Product Hunt 每日热榜 2026-08-19

PH热榜 | 2026-08-19

#1
Astute
Automate your B2B brand going viral, with new media creators
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一句话介绍:Astute 是一款面向B2B企业的“新媒体创作者合作自动化平台”,通过AI代理监测全网新媒体讨论、生成数据驱动的创作者匹配策略,并自动完成从外联、签约到付款的整个合作流程,解决品牌方传统营销失效、手动管理创作者合作繁琐且难以衡量ROI的痛点。
Social Media Marketing Artificial Intelligence
B2B新媒体营销 创作者经济 AI营销代理 网红营销自动化 品牌传播 数据驱动策略 ROI归因 社交媒体监测 内容合作管理 SaaS平台
用户评论摘要:用户最关心归因与衡量问题:多位评论者指出在iOS邮件、应用内浏览器中referrer丢失导致转化归因困难,创始人回应已通过UTM参数、首方cookie及“AI引擎可见度”和品牌资产值补充衡量。此外,用户询问平台具体如何匹配创作者,以及未来向“自有受众建设”扩展的方向。整体反馈积极,认可团队背景与痛点抓取,但无重大功能建议或批评。
AI 锐评

Astute的叙事很漂亮:踩着广告、SEO失效的焦虑,声称用AI代理接管B2B创作者合作全流程。但剥开“AI”外壳,底层逻辑仍是传统的“资源撮合+自动化外联”,其真正的护城河不在于技术,而在于是否真能积累足够高质量的专属创作者网络和颗粒度足够细的匹配数据——这需要长期运营,而非一个pre-seed和16,000个注册者就能验证。评论区最犀利的质疑直指归因:当移动端referrer被系统剥除,大量点击沦为“直接访问”,所谓“衡量ROI”仍是概率游戏。创始人承认“不追求完美归因”是务实的,但这恰恰暴露了产品价值主张中“measurable ROI”的硬度不足。另一个隐忧是:Astute想同时服务品牌方和创作者,双边市场最难的是冷启动,而产品目前靠创始人个人IP和EF圈层获得早期口碑,能否复制到大众市场存疑。AI代理自动化了“签约”和“付款”,却无法解决创作者内容质量不可控这一根本风险——一个数据匹配再精准,创作者口碑翻车就能毁掉品牌信任。Astute真正的机会不在替代人力,而在于将“新媒体分发”变成可预测的渠道,但这条路比“自动发邮件”难一个量级。当前产品更像是一个“精心包装的优质利基CRM”,距离“新媒体的程序化购买平台”还有相当距离。

查看原始信息
Astute
Astute is the first B2B new media platform, starting with creator partnerships. We monitor your presence in the new media, build a data-backed strategy around the creators your buyers trust, and run the partnerships on autopilot. All within minutes.

Hey everyone!

My name is Vida, and I am the Founder and CEO of Astute (www.joinastute.com). 👋

A bit of context on us: I ran growth at Fluidstack through the $2M to $2B stage, @abhishek_manikandan was an ML engineer at The Trade Desk. We met at EF London and just closed an oversubscribed $1.2M pre-seed from VCs and angels to build the first B2B new media company, starting with creator partnerships.

As a B2B marketer, I knew that the marketing playbook (ads, PR, SEO) doesn’t work anymore. At Fluidstack I quickly realised that our audiences weren’t clicking on our ads. Instead, they were reading Substacks like SemiAnalysis, listening to podcasts like Acquired and TBPN, and scrolling on LinkedIn and Twitter. 

Every team I speak to already knows this. But most can't activate this channel today, because it takes months of manual searching, cold outreach, and back-and-forth, with most of it going nowhere. 

Even the current tools in the space don’t work in the way that brings value. As a marketer, and now a founder, I want to understand the best types of creators, the optimal audience size, best performing platforms - for my company. I want a personalized data-backed strategy. And then I just want it all done for me. I don’t mind investing $10k in creators who will bring me customers, but I don’t have the bandwidth to manage the CRM, comms, payments. All the current players fail to understand this.

On top of that, most offer only ad slots, but the real value is in an endorsement or editorial partnership with a creator. But editorial partnerships are difficult to productize. They lead to organic content which is why they require a higher volume of granular data from both sides, to ensure the right match. Competitors haven’t cracked this - we have, with over 16,000 creators in our proprietary network.

So we built Astute. We have two AI agents - one is a new media manager for B2B companies, the other is a talent manager for creators.

How it works

  1. Astute first listens. Astute monitors over a million creator posts every minute and surfaces where you, your competitors, and your category are being discussed, including the specific threads worth engaging with.

  2. Then it builds a strategy. 1,000s of data points turn into a creator strategy specific to you: who your buyers already follow, which audiences overlap with your ICP, and what a realistic first three months looks like.

  3. It handles the partnerships. The manager agent searches the 16,000 creators on the talent side - people with loyal, high-intent audiences on Substack, podcasts, LinkedIn and X - picks the right ones, and locks in the partnerships once you approve. Editorial features, podcast guest slots, newsletter ads, event collabs, and more.

  4. And it measures ROI. Impressions, conversions, brand mentions, and visibility inside AI search engines.

But this is only the beginning. We are going after the full new media stack. We want to build a space where every B2B company will come to build their brand, legitimacy, and an owned audience in new media.

Now the juicy stuff - our Product Hunt deal

Finally - HUGE thanks to @vedranrasic for hunting us today 🚀

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@abhishek_manikandan  @vedranrasic  @vida_stanic1 Tracking ROI on podcasts and LinkedIn has historically been a black box, are you relying on unique landing pages and promo codes or using probabilistic attribution models for conversion tracking? congrats for launch 🙌

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@abhishek_manikandan  @vedranrasic  @vida_stanic1 How does Astute data help brands decide which creators are the right fit for their campaigns.

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@abhishek_manikandan  @vida_stanic1 Excited to be on this journey with you

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The measurement side is where I'd expect this to live or die, and it's harder than it looks. I built proper attribution on my own site last week and the thing that surprised me is how much creator and social traffic arrives carrying nothing at all: messaging apps, iOS Mail and in-app browsers strip the referrer, so a meaningful share of my signups log as "direct" and I genuinely cannot tell which post caused them. For a B2B buyer the first question is going to be which partnership produced pipeline. How do you attribute that when a lot of the clicks arrive anonymous by construction? If you've solved that cleanly it's a bigger selling point than the automation.

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@ofirsmol Hey Ofir - accurate attribution for everything is super hard. We've seen the same issue - we solved for it in 2 ways:

1) We track through UTM tags all traffic each individual creator brings you. Tbh it was a technical challenge to set this up - but we did because we knew it was important.

2) We also track impact on the AI engine visibility and brand earned value - which are 2 things that are as important when it comes to creator campaigns, but no one tracks them.

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@ofir_smolinsky Definitely agree this is one of the hardest and most important problems for us to get right.

The goal right now isn’t to pretend we can attribute every single signup perfectly. It’s to give a B2B team enough evidence to answer: which creators are actually influencing pipeline, and where should I put the next dollar?

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@ofir_smolinsky Honestly this is the right question to push on. You can't recover a referrer that was never sent, so we don't try. What we lean on is the stuff that survives an in app browser or an iOS Mail click. The parameters travel in the URL itself, not in the referrer header, so a creator's tracked link still lands with its source attached even when the referrer arrives blank. Same for promo codes and the landing side tag, which are first party and do not care how the click got there.

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Hey - I'm Abhi, the Founder and CTO of Astute!

Before Astute, after graduating from Oxford Uni (CS), I worked as an ML engineer at The Trade Desk, but on the side I ran a B2B engineering YouTube channel that ended up doing 15M+ views (itisAbhi on YT). I've personally received 100s of partnership emails from brands.

And to be honest, I said no to almost all of them. Not because I didn't want to work with companies, but because saying yes meant weeks of back-and-forth, contracts, chasing invoices... And with a lot of companies I also didn't want to work, because they were not relevant to my content at all. It made zero sense.

So when we started building Astute I was really excited to fix that side of the problem. The creator side. We built the talent manager agent I wish I had. And over 16,000 creators in our network are already using it!

Happy to go deep on how any of it works - the matching, agent architecture, whatever. All questions are welcome!

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@abhishek_manikandan I don't say this enough but I also have to flag how lucky I feel Abhishek is my co-founder. Not only is he a perfect person to be building in our space (ex creator!), he's an incredibly talented and hardworking ML engineer, but also an incredible human. Kudos to him!

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@abhishek_manikandan your a rockstar! So impressed watching you perform on little sleep and monster energy to get us to launch.

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Hey all - Founding Engineer @ Astute here!

When @abhishek_manikandan and @vida_stanic1 told me what they're building - I knew I had to get on this. My family runs a big media company in my home country - so I REALLY get this.

I've been working mainly on the social listening and media monitoring element of the platform, which all powers our data strategy. Feel free to shoot over any questions you may have for me :)

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@ishan_kalra1 has literally been sleeping in the office to get us to launch!

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Super excited to hunt this one.

I run LeadDelta (PH SaaS of the Year 2022), so I live inside B2B distribution all day. Somewhere in the last 2 years, the answer to "where did this deal come from?" stopped being an ad. It's a newsletter now. Or a podcast. Or someone on LinkedIn my buyer has been following for three years. Everyone I talk to knows this is happening.

So when Vida showed me Astute I got it immediately. 

The more I got to know her and her co-founder, the more I realized there isn’t a better team to build this company. Vida spent years at Fluidstack helping grow the company from $2M to $2B using this exact channel! Her co-founder Abhi was a creator himself - 15M+ views on YouTube is HUGE - he's literally the guy on the other end of the partnership emails.

Vida and Abhi are around all day, ask them anything. 

Congrats on the launch team! Proud to be a customer (and Hunter!).

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@vedranrasic Thanks so much for hunting us today Vedran!

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@vedranrasic Thank you for the support and all the advice you keep giving us. Great to have you as a mentor.

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@vedranrasic Thank you for hunting us Vedran! As someone who produced engineering content, I saw firsthand the value of tech companies reaching their audiences through creators they trust - and we want to make doing that as easy as talking to your agent with Astute. We really appreciate your mentorship!

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It was a WILD RIDE working on Astute with @vida_stanic1 and @abhishek_manikandan, especially the past few weeks leading up to our launch!

I am so excited to share what we've built with the world - it's really a game changer for Founders and Marketers!

Feel free to @ me with any technical questions :)

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@abhishek_manikandan  @shehroz_astute So lucky to have you on board, you're brilliant!

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Super cool! Love the direction. In the past few years, I noticed that all kinds of marketing simply repel me, and I don't trust the product. A lot of the ads and SEO are AI slop anyway. But when I see someone I read, e.g., Lenny or Pragmatic Engineer, share some tool, I instantly get a thought: "Wow, why haven't I tried this before?"

Congrats on the launch!

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@perevoznyk_m Thanks Mykhailo! Really appreciate it :) and to be super honest, I couldn't agree more. At one point I was prepping a script for one of our videos that we were shooting and I had a line about how "bad marketing makes me sick in the stomach". I think there is SO little that a) looks good b) does the job now in B2B marketing. Creators really are it.

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@perevoznyk_m The decision making process for purchasing software is definitely changing and collaboration with trusted voices is now key.

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@perevoznyk_m Completely agree! I chose the tech stack for Astute based on creator suggestions, because of the trust I had in them - and the same is the case for B2B audiences. As someone who previously worked in adtech, and the direction AI slop is taking it, this trust-based marketing for B2B companies really is the future.

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@vida_stanic1 Astute is amazing product and you deserve PH #1 spot today. Keep the good work!
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@igor_stankovic Thanks Igor!! Appreciate your support :) We love yall at LD!

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@vida_stanic1 Congrats on the PH launch and the $1.2M raise.. Anyone who has tried to run creator partnerships manually knows how much of it is chasing contracts and invoices.

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@umar_lateef Thanks Umar - you're the 1,001st person to tell us this. And I've been there when I was at Fluidstack. So completely get it, so painful. For me personally the worst part was actually uploading invoices in the bank or having to manage payouts...Astute now automates all of this which is great even for me when we partner with creators :)

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@vida_stanic1  @umar_lateef And this is by far one of the biggest reasons why we're building this! We spent many sleepless nights ensuring our agent can autonomously outbound, pitch, collect payment and report on the placement, eliminating all the manual lift you previously needed to do.

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The amount of time as founders we’ve spent trying to go viral is unreal. Perfect team for a massive problem, congrats guys!

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@saaras_mehan Thanks Saaras! We've really enjoyed working with Jack and Jill and yourself. Thanks for the support :)

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@saaras_mehan Thanks for your support Saaras! Also I can't speak highly enough of Jack & Jill.

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As a creator, this immediately caught my attention. Excited to see brands and creators connect in a more meaningful way!

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@istiakahmad Thanks Istiak! Make sure to sign up to the platform as a creator. We don't charge any fees to creators or take a percentage of their earnings. Looking forward to @Astute sending B2B brand collaborations your way.

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@istiakahmad Wow thank you! This is one of the best feedback feel-good-moments we can get as founders! Really appreciate it and we are super grateful to have you in our network and community :)

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Creator partnerships are becoming a major growth channel, and Astute is building the infrastructure to make them much easier.
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@priyankamandal Thanks Priyanka! That’s exactly how we see it. The opportunity is huge, but the infrastructure around B2B creator partnerships is still incredibly fragmented. We want to make it as easy and repeatable for companies as running any other growth channel 🙌 And creator partnerships are just the beginning. There’s a lot more coming as we expand what Astute can do across new media 🚀

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@priyankamandal Hey Priyanka - couldn't agree more. When we look at who humans trust, it's a no brainer. But even AI agents shopping for humans index creator content highly. To win in the future of where discovery is going, companies will have to work with creators for distribution and legitimacy.

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Congrats on the launch team! Curious to understand as Astute expands beyond creator partnerships, what other parts of “new media” do you see the platform helping companies manage?

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@florian_van_schreven Thanks Florian - I know Uizard did really well with launches several times :)

Re your qq - I think there's an a16z article that explains into a lot of detail all parts of new media, and a lot of our thinking resonates with that. To summarize it here: it's all about distribution in channels that matters.

For us that means 2 things:

  • distribution with creators who own your key audiences already

  • building your own loyal audiences

We help companies with the 1st now. In terms of the 2nd - our main goal is to do it in a data-backed way. Never been done before - data backed brand building. But we have a unique ability to help companies from the get-go know which new media platforms, channels, messaging, etc. will work for them. Next phase is expanding into that area and helping with execution.

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@florian_van_schreven Thank you Florian, and great question! To bring a technical angle to the answer, the key to unlocking distribution with creators who reach your key buyers, as well as building your own 1st party audiences, is building a real-time engine of proprietary data that can fuel optimal placements.

This would include, for all the various segments that compose a company - industry, size, location, funding, past brand ethos and more - we collect, for both third party and first party placements, 1000s of data signals that link the performance (CTR, conversions, EMV, AEO, and much more) with the exact content and type of placement, scoped to a specific time frame. This would allow us over time, for any B2B company, to be the ultimate source of how exactly a company should go about their new media strategy - what content they should post, when and where, as well which creators they should work with and why. Composing all of this together into an end to end agentic solution is what would eliminate not only the painful manual lift, but the overall confusion that companies go through when they attempt to solve this!

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All the best Rizwan.
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@mustapha_ajermou1 Thank you! Really appreciate the support. Excited to try out @AutoReels.Ai

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Big congrats on the launch! Automating B2B brand virality through new media creators is such a powerful angle given how fast distribution tactics are shifting right now. Love seeing tools that help founders tackle creator-led marketing without the usual operational nightmare. Wishing the team massive momentum today!

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@thisiskp_ Thanks so much KP, really appreciate your support. NGL I just told my team that the Head of Community at Netlify has supported us and they lost their minds! Also I made my first ever deployment on Netfify (a personal vibecoded project) :))))

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@thisiskp_ Thank you! As someone who has used Netlify many, many times to deploy my various projects over the years (still a massive fan of its simplicity), it's honestly an honour to be supported by you guys! And I completely agree - the distribution tactics for B2B marketing are aggressively shifting, and we want to enable companies to capture the effectiveness of new media marketing.

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@thisiskp_ Really appreciate this, KP. One of the big things we want to change is the idea that creator-led marketing has to be a series of one-off sponsorships. We think it can become a repeatable, measurable distribution channel for B2B companies, in the same way teams think about paid or outbound today.


Coming from someone who understands community and distribution so well, your support means a lot 🙏

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Looks super exciting!! Congrats on the launch, will send to my team

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@henry_pulver Thanks so much Henry, love your work btw :)

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@henry_pulver Thanks for the support Henry!

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@henry_pulver Thanks Henry! As someone obsessed with product, have just been having a look at Superflows too - really curious to try it out for UX!

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See you there for the 2nd time. You are nailing your distribution! :D :)

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@busmark_w_nika It'd be very concerning if I didn't, what with being a distribution platform :)))

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@busmark_w_nika Thanks Nika! also great to discover @minimalist phone: reduce your screentime I definitely need this.

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Congratulations on the launch of Astute! (and a terrific launch video!) Compared to B2C, B2B has a lot of catching up to do due to the shift in marketing from the old playbook to how audiences now consume media. Very excited to watch your journey! @vida_stanic1 @abhishek_manikandan

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@abhishek_manikandan  @randy_fn Thank you so much Randy - I could not agree more. B2C marketing has been a bit epic over the years. B2B on the other hand had to follow the professional "norms". But I think we all now know where attention is and that we need to grab it. Just have to find a way to do it - which Astute is :)

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@vida_stanic1  @randy_fn Completely agree - it's about time B2B makes use of creator marketing, in our opinion one of the most effective channels for gaining trust in B2B buyers. B2C marketing can get away with nurturing impulsive purchases with paid ads, but for a six figure B2B contract, it's vital to earn that trust. Previously you could do this with PR; but in this age of new media, creator partnerships are how this will be done, and we're building Astute to pave the way for exactly that.

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Congrats on the launch, @vida_stanic1 and @abhishek_manikandan !

The B2C market has already proven the creator economy is massive - I actually believe the B2B opportunity is even bigger, there just hasn't been a tool that makes it possible until now.

That's exactly why Astute clicked the moment I saw it. Excited to watch this take off.

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@abhishek_manikandan  @kristian_asani Thanks Kristian! We're so excited to be backed by Silicon Gardens. You and the team have been incredible at every step of our journey so far. Excited for what's to come!

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@vida_stanic1  @abhishek_manikandan  @kristian_asani Thank you for the support Kristian, the shift in how products gain awareness and get purchased has definitely shifted to channels where trust is higher.

@astute is helping to fill that gap for B2B companies unsure how to activate this channel.

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@vida_stanic1  @kristian_asani Thank you Kristian! Completely agree - the creator economy has been tremendously successful in B2C, but in a world where developing trust niche, high-intent audiences that convert into large contract sizes is crucial to company's growth, I struggle to see how the B2B opportunity isn't even bigger. Really excited for the journey ahead!

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This is a problem I’ve run into countless times myself: you know the audiences you want to reach are listening to podcasts, reading newsletters and following creators, but actually finding the right people, figuring out who to work with and managing everything is incredibly manual.


So excited about what @vida_stanic1, @abhishek_manikandan and the @Astute team are building. A problem I genuinely wanted solved. Huge congrats on the launch 🚀

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@abhishek_manikandan  @rizzykicks Lucky to have you on our team!

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B2B creator marketing definitely needs something like this. Excited to explore Astute and see what’s possible.
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@imtiaj_ahmad Thank you so much for saying that! If you have any feedback, please do share to vida@tryastute.com :)

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As a creator, this immediately caught my attention. Excited to see brands and creators connect in a more meaningful way!

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Congrats on launch @Astute 🚀
Interesting! Does this work well for startups too? Do you have any special packages for startups?

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@gor_geghamyan Thanks Gor!!!

I'd say startups are our sweet spot. They usually don't have their own audiences for distribution, and they have to find other ways to reach buyers/hires/investors/partners. That's where we come in.

In terms of packages - our Starter plan at $199 is suuuper startup friendly and crafted for companies just starting their new media journey

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Pretty cool! Congrats on the launch@vida_stanic1 and the Astute team. Love the video!

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@preetraj Thanks Preet! Video was inspired by the Big Short :)

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Yep, putting right companies in front of a right audience with the relevant message - might sounds simple but the devil is in the details, as usual. And such a massive pain - already registered!

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@yermolenkoa I'll be mega honest here and overexpose a bit - I thought it'd be waaaaaay simpler than it is. You are 100000% right - devil is in the detail. Thanks for signing up :)

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@yermolenkoa Welcome aboard! From the engineering side you are completely right that the devil is in the details, and the specific detail is the match. Right audience means knowing that a particular newsletter's readers are your buyers and that the creator has actually covered your category, not just that they have a big following. That is where most of the data work went, and it is what makes the agent's picks hold up once the partnership is live. Would love to hear how it goes for you, feel free to shout if anything comes up.

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Congrats! Really excited for this

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@garygao Thanks Gary! You know we love Chert at Astute - and will be a loyal customer for a VERY long time :)))

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@garygao Thanks Gary! Happy to jump on any calls and run you through it should you need any help.

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@garygao Thanks Gary, really appreciate it! Speaking as the engineer who got to wire Chert into our stack, it has been a genuine pleasure to build on. Love what you are doing over at Chert and the direction you are taking it, going after iMessage is such a unique angle and nobody else is really doing it properly. Cheering you on!

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Really interesting approach! Turning creator partnerships into a data-driven, automated process for B2B sounds very promising. Love the idea of making something that usually takes a lot of manual work much faster and more scalable.
Good luck guys!

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@adana Hey Adana - wow this means a lot coming from you :))) I actually couldn't agree more on the data-driven element of it. I was a growth marketer before this, so we just built a tool I wished I had.

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@adana Thanks Adana! The faster and more scalable part is the fun bit to build. The manual version of this is a growth person living in spreadsheets, DMs and invoices for weeks. We moved all of that onto two agents that talk to each other, one managing the company side and one managing the creator side, so the search, the negotiation and the payment happen in the background and the team only steps in to approve. Appreciate the good luck!

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Great problem to solve! One question i was wondering when looking at your pricing page - how are creators charged? Is this included in the plans or paid separately? Best of luck today!
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@urh_meza Hey Urh - unlike EVERY other platform, we don't monetize from creators. We don't charge them $ or %, nothing!

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@vida_stanic1 that’s great! What about from a business perspective? Does a business pay for a subscription and creators separately?
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@vida_stanic1 yes, that’s what i imagined. From a conversion optimization point of view that would be the question that pricing page should answer more clearly in my opinion. At least that is one of the key questions i would wonder when comparing different platforms and deciding which to dedicate to. Otherwise looking great!
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Creator partnerships are becoming a major growth channel, and Astute is building the infrastructure to make them much easier.
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@priyankamandal Thank you Priyanka, I think creator partnerships will become the biggest lever for growth in companies. And I don't mean just buyers / customers - I mean full growth. Hiring, fundraising, building a strong brand. Creators bring you these audiences, and credibility.

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@priyankamandal We got so much more to come too. New Media will be the distribution channel of choice for all B2B companies.

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Experiencing this problem right now, trying to find + manage specific creators for a campaign. Can't wait to try!

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@sami987sa Hey Samir, wow our timing is GOOD. Please use code PRODUCTHUNT and you'll have free trial until the end of this month :)

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@sami987sa Can't wait for you to try it out! Our matching engine uses an extended agentic RAG pipeline, combined with many enrichment layers to serve you the best matches, tailored exactly for your company. And the best part is - anything you don't like, you just tell the agent and it will refetch and sort it out for you!

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@sami987sa Let me know if you need any help. Happy to jump on a call with you.

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#2
Clipto MCP
Let agents source clips from terabytes of your local video
368
一句话介绍:Clipto MCP 让 Claude、ChatGPT 等 AI 智能体通过语义搜索,直接"看懂"并调用你电脑本地存储的海量视频、照片和音频素材,无需手动翻找文件即可完成找素材、剪粗剪、搜会议等任务,解决了个人媒体库内容无法被 AI 理解和利用的痛点。
Productivity Search Video
AI视频搜索 本地媒体管理 MCP协议 AI智能体 语义搜索 视频剪辑自动化 私有化数据处理 媒体索引工具 创意工具
用户评论摘要:用户多肯定其解决找素材痛点和本地隐私优势,核心疑问集中在:海量库(TB级)下的索引速度和搜索性能稳定性;对杂乱文件名/混合格式的兼容性;对 Claude 与 Cursor 的兼容性;是否支持 NAS/外置硬盘及 API。开发者反馈积极,提出增加情绪、景别等语义过滤和自定义标签体系建议,并演示了零人工干预剪出马斯克MV的案例。
AI 锐评

Clipto MCP 的巧妙之处在于它卡位了当前 AI 智能体的核心盲区——大模型能读文件,但读不懂非结构化媒体内容。过去半年,Agent 的文件操作能力突飞猛进,但对 TB 级视频、录音的"理解"几乎为零。Clipto 试图在本地建立一座连接"媒体原始数据"与"语义逻辑"的桥梁,本质上是将个人媒体库重构成一个可供 Agent 查询的向量数据库,这确实颇具前瞻性。

然而,冷静审视,其宣传的"让AI自动剪出马斯克MV"更像是精心设计的魔弹。FFmpeg 拼接和歌词匹配属于确定性任务,真正的过滤器其实是在 Clipto 完成的转写和语义分段。Demo 的惊艳不代表实际工作流的高效:用户真正刚需的是"精准回找"和"粗剪预排",而非猎奇性的音乐视频。最大的坑在于索引成本——24小时处理2TB数据看似快,但对于普通用户动辄十年的家庭影像,这意味着首次使用的周末必须持续开机,且这一过程计算资源消耗巨大。

真正的商业壁垒不在面向 C 端的搜索体验,而在于 MCP 协议带来的 Agent 生态绑定。一旦创作者习惯了让 Claude 通过 Clipto 精准找到素材,迁移成本将极高。不过,尽管产品定位足够锐利,但现阶段的回复中充满了对"MCP未来可能"的承诺——情绪/景别过滤、NAS支持尚且是"雷达上",说明产品仍处于尝鲜期。对于严肃的视频工作者,它当前更像一个高效的素材管理库,而非替代剪辑软件的工具。若后续能开放 API 供下游软件直接消费其语义标签,或许能真正从工具跃迁为媒体基础设施——否则,极易沦为大型 AI 玩具。

查看原始信息
Clipto MCP
Clipto MCP gives Claude, ChatGPT, and other AI agents the ability to source clips and more from inside the videos, photos, and audio recordings stored on your computer. Instead of manually browsing files, simply describe what you need. For example, turn a script into a video by matching each sentence with your local footage; find every scene where someone mentioned a topic; create rough cuts; or search years of media as if you have a dedicated assistant editor.

Hi Product Hunt! 👋 Henry here, a few months ago, I launched @Clipto , a fully local AI media search engine that helps people search terabytes of videos, photos, audio, meetings, and documents using natural language.

Since then, one request kept coming up:

“Can Claude use Clipto?”
“Can ChatGPT search my media library?”
“Can my agent actually edit videos using my own footage?”

Today, we’re excited to launch Clipto MCP.

AI agents can already access your files. What they can’t do is understand what’s inside terabytes of media.

That’s what Clipto MCP changes. It gives AI agents semantic understanding of your local media, so instead of manually browsing folders or scrubbing through timelines, you can simply describe what you want.

Some examples:

🎬 Turn a script into a video by matching every sentence with relevant footage.

🔍 Find every clip where someone mentioned a specific topic.

🎤 Search years of meetings for a decision or discussion.

✂️ Generate rough cuts from thousands of hours of video.

Everything runs on the media already stored on your computer. No uploading your library to the cloud.

This is only the beginning. As AI agents become more capable, they’ll need more than file access. They’ll need to understand the content inside our personal media.

To celebrate our launch, we're offering 1 month free to anyone who signs up this week with code PHLNCH.

We’d love to hear what you’d build with Clipto MCP.

We’ll be here all day answering questions and collecting feedback.

Thanks for giving it a try! 🚀

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@henrykang As a fellow founder, respect the scope you shipped 🙌 what's next on the roadmap?

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One more experiment we wanted to share because this one surprised us.

We downloaded a bunch of Elon Musk interviews, indexed them in Clipto, connected the library to Claude through Clipto MCP, and basically asked:

“What would be something fun to make with all this footage?”

Claude came up with the idea of turning Elon into a music video using Daft Punk’s Around the World.

From there, the whole thing ran automatically.

Clipto had already analyzed the footage in detail, turning every interview into structured, searchable media with transcripts, speakers, scenes, and precise timestamps. Through Clipto MCP, the agent could understand and retrieve exact moments across the entire library.

Claude analyzed the song, decided where Elon’s words could fit, asked Clipto for the matching moments, picked from the results, and assembled the final video with FFmpeg.

We didn’t manually select the clips or clean up the result. What you see here is the first output:

Raw output: https://youtu.be/sNLo3_-ybiQ

Want to try it yourself? We packaged up the same Elon interview clips we used, so you can download them and run your own experiment.

Elon Interview Library — the same footage we used for this experiment. Try a different prompt and see what your agent comes up with.

https://www.clipto.com/mcp/demo-library

We also put together a B-roll library if you want to try something completely different.

B-roll Starter Library — 1,000 royalty-free clips across people, work, cities, travel, nature, and more. Use them to experiment with your own ideas and workflows.

https://www.clipto.com/mcp/demo-library

Or connect Clipto MCP to your own media and see what your agent can make from the footage you already have.

We’d love to see what your agents come up with.

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@henrykang The interesting part here isn’t giving agents access to your files. They already have that.

It’s teaching them where the good stuff is.

Once an agent can search years of footage, meetings, and recordings by meaning instead of filenames, the humble media library starts looking less like storage and more like a database nobody knew they had.

And turning that into video edits is where things get particularly interesting.

The next question is probably what happens when the agent stops searching and starts deciding what’s worth keeping.

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Really curious how well the semantic search performs once you throw a huge media library at it.

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@sylvialane That’s exactly the scale we built Clipto for. We’ve tested it on multi-terabyte libraries with years of footage, and keeping search fast and relevant as the library grows has been a big focus for us. Would love to hear how it performs on your library if you give it a try!

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congrats for the launch! this is really helpful, I can imagine starting a project in Claude and asking it to find all the relevant material before I even open my editor 👀

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@brattyaiguy Exactly! That’s one of the workflows we’re most excited about. Start with the idea, let the agent understand your project and source the right moments from your entire media library, then bring those clips straight into the editor. Thanks for checking it out!

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congratulations! what has been the most surprising use case you have discovered while testing agents with large personal media libraries?

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@avery_thompson2 Avery, thanks! Check out my other comment about our experiment with Elon Musk's interview clips. That's one of the surprising use cases: AI figuring out something creative based on all the media library, even beyond my expectation!

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Meeting recordings might be the boring use case here, but honestly probably one of the most useful.

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@jianqiang_hao Exactly. Meeting recordings may not be the flashiest use case, but they’re probably one of the most practical. You can import a recording into Clipto for local analysis, or start recording directly in the Mac/Windows app. For sensitive meetings, keeping the recording and analysis on your own Mac(or PC) can make a real difference. We hope this makes things easier for anyone who needs to keep their conversations private. Thanks for calling this out!

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I’d be interested to see this with a really messy archive — random filenames, old projects, mixed audio and video.

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@sancijun That’s the kind of library Clipto is built for. Filenames and folder structures only help when you already know what you’re looking for. Clipto looks at what’s actually inside the files, so even a messy mix of old projects, audio, and video can become searchable through natural language.

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Does this work the same way with Claude and Cursor?

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@erok_chen yes, it is the same. Just download the Clipto app and install the MCP for the corresponding agent.

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I can see this fitting really naturally into an editing workflow. Find the right clips first, then build from there.

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@lily_liu8 Exactly. Finding the right clips is often the hardest part. Once agents can understand and source from your entire media library, there’s a lot more they can help with downstream. Thanks Lily!

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Looks cool! How well it handle the large media libraries ? Does performance stay consistent when searching through tb of files ?

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@farhan_nazir55 Good question! Once your library has been indexed, search performance stays fast and consistent, even across terabytes of media. The more challenging part is the initial analysis and indexing. We’ve added several processing modes so you can balance speed and system usage, allowing Clipto to work through a large archive in the background while you continue using your Mac/PC normally.

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The “find this moment in my footage” use case is probably the first thing I’d try.

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@new_user___1282025165cc92287e7a197 That’s probably the best place to start :) Just describe whatever you remember about the moment, even if you have no idea which file it’s in. Thanks Yiyao!

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This could be useful for research too, especially when your source material is mostly video and audio rather than documents.

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@bioyue Absolutely. A lot of valuable knowledge is trapped in video and audio, while most AI research workflows still work best with text. Making that media searchable and understandable to agents opens up some really interesting research workflows. Thanks Bio!

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Congrats @henrykang and the team on the official PH launch of Clipto MCP! 🎉 I’ve been following since your first release, and this MCP upgrade is a game-changer – the idea of letting AI agents "understand" terabytes of local media instead of just accessing files is brilliant. "Turn a script into footage" and "search meeting decisions" are killer use cases for creators and teams alike.

Huge props for keeping everything 100% local (privacy first!) and that 2TB/24hrs indexing speed on M5 is seriously impressive. 💪

One concrete suggestion: since MCP is all about agentic workflows, could you add semantic filters like "emotional tone" (e.g., excited, serious) or "shot type" (close-up, wide) for more nuanced retrieval? Also, custom tag hierarchies (project + client) would make enterprise adoption much stickier.

Quick question: any plans to support shared indexing across NAS or external drives? Or maybe a lightweight API for developers to plug into tools like Notion? I'd love to see how far this ecosystem can go.

Wishing you a huge launch! 🔥 Can't wait to hear your thoughts!

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@rocsheh Thanks Zepeng! Really appreciate you following us since the first launch, and you nailed the distinction we care about most: access to files is relatively easy now, but understanding what’s actually inside years of media is a very different problem.

Love the semantic filter idea. We’re already extracting much richer information than just transcripts, and things like shot type, emotion, people, scenes, and other visual context are exactly the kind of signals we want agents to be able to reason over.

NAS and external-drive workflows are also very much on our radar, especially for professional media libraries where terabytes quickly become tens or hundreds of terabytes. And on the developer side, MCP is really just the beginning. We’d love to make Clipto’s media understanding useful well beyond the Clipto app itself.

Thanks for the thoughtful feedback and for being with us again for this launch! 🙌

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The Elon/Daft Punk demo is wild lol.

How much manual cleanup did you actually skip vs what Claude + FFmpeg pulled off on its own?

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@boyuan_deng1 Thanks Boyuan! ;) actually that's the point, we left everything to Claude, the video was produced with zero-human-touch. We are preparing the Elon Musk's clips so you can give it a try.

Check back here in a couple of hours.

https://www.clipto.com/mcp/demo-library

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Documentary editors sitting on hundreds of hours of footage are probably going to appreciate this one.

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@yuchengjee Absolutely. Documentary was actually one of the use cases we had in mind from the beginning. When you’re sitting on hundreds or even thousands of hours of footage, being able to ask an agent for a specific moment instead of scrubbing through it all can completely change the workflow.

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The local search part is what caught my attention. Being able to ask an AI tool to find something across your own media library feels genuinely useful.

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@shirley_mou Thanks Shirley! That’s exactly the idea. Your media is already there, but finding the right moment across years of footage is still surprisingly hard. We want to make that entire library something you can simply talk to, whether directly in Clipto or through your favorite AI agent.

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Such a smart idea that addresses a real pain point. The hardest part of putting together a demo video is looking for that particular screenshot called "Screenshot 2026-08-19 at 12.04.44 PM" or video named "858551D6-F8A4-4CE0-9A71-DC6EF6DDD2A5" 🤦🏻‍♀️

I'm excited to try Clipto's NPL search for this and curious if the tags work!

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This feels especially useful for projects where the context is spread across dozens or hundreds of files.

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Congrats on this launch! Amazing product!

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@peng_wood Thanks Wood. Really appreciate the support.
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I like the new use case for the application! Because photos are easier to store than ever, I find it harder to find what I'm looking for in my camera roll than before.

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@sseanyd Exactly. The easier it becomes to capture and store everything, the harder it becomes to find a specific moment later. We want you to simply describe what you remember and let Clipto find it for you. Thanks sean!

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Congrats on the second launch. That music video went out as the raw first output, no cleanup at all. Takes some nerve to show the actual thing rather than the polished version.

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@lucasjpols Exactly. We wanted to show what Clipto MCP and an AI agent can actually produce on their own today: understand the creative direction, find the right moments across a large media library, and assemble them into an editable rough cut. A polished version would have looked better, but it would also have hidden where the product truly is. What matters most here is being able to pinpoint the exact moments you need across huge, complex libraries and turn them into a useful starting point for editors.Thanks Lucas!

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This is so cool, I desperately needed something of this sort for so long

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@maunilparikh So glad this resonates. We built Clipto for exactly that feeling—knowing the moment exists somewhere in your library, but having no practical way to find it. We’ve included an invite code on our Product Hunt page that gives you a 30-day free trial. Give it a try and let us know what you think. Thanks Maunil!

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@maunilparikh Thanks! Please give it a try! Would love to see what you create!

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Sourcing clips from local video terabytes using AI agents is a huge time-saver. Congrats on bringing this to life!

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@thisiskp_ Thanks! That’s exactly the idea. Once a media library grows into terabytes, finding the right clip can take longer than editing it. We want agents to understand your entire library and bring back the right moment in seconds.

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It’s pretty mind blowing that it can work with local files like this. Is the multimodal model understanding the content? If that’s the case, I could feed my local videos directly into it for editing. That would really boost my efficiency. Honestly, this would’ve been unthinkable just a year ago!
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@zenda1122 Yes, that’s the key. Clipto uses multimodal models to understand what’s actually inside your local video and audio, not just filenames or transcripts.

It’s amazing how far AI has come in just one year. We’re working hard to turn that progress into something genuinely useful for real workflows like this. Once your media is indexed locally, MCP lets you bring that understanding into the AI tools you already use, opening up a lot more possibilities. Thanks!

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I’d love to see more examples of Claude or Cursor taking the retrieved content and turning it into a finished project.

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@rydensun Thanks! That’s where combining Clipto with Claude or Cursor opens up a lot of possibilities. We’ve added some recommended prompts in both the app and on our website to help you explore these workflows.

For anyone who wants to try it but doesn’t have enough footage ready, we’ve also prepared a starter library with 1,000 general-purpose clips. You can download it here:

https://www.clipto.com/mcp/demo-library

We’d love to see what you create!

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As someone with TONS of footage, not the best file organization (to be kind to myself about it) and content creation as a side project, I am really excited to try this one, congrats on the launch!

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@denitsapenchevavaltchanova It sounds like Clipto could be a great fit for your workflow. You shouldn’t need a perfect folder structure—or spend your limited side-project time organizing files—before you can use your footage. Just describe the moment you remember and let Clipto find it.

You can also use our invite code to get a one-month trial. We’d love for you to give it a try and share any feedback or suggestions. Thanks so much!

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Pretty cool and handy. Keeping everything local is a big plus.

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@henry_habib Thanks! Keeping the media library and indexing on your own Mac was important to us from the start. Your personal footage can be incredibly useful to AI, but it should always remain under your control.

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The demo where the agent finds the relevant material and keeps working from it was probably the most interesting part.

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@mingyouagi Exactly. Finding the right material is only the first step. Once the agent can understand and pull from your media library, it can keep working instead of stopping at a list of search results. That’s where it gets really interesting—when the world’s most capable AI meets your own media and memories, entirely new possibilities start to open up. Thanks!

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Being able to search across local video and audio through natural language could save a ridiculous amount of time.

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@1251912798 Exactly! And with MCP, it goes one step further — your agent can find and use those moments for you, not just help you search.
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The editing example got me thinking about how much time is wasted just hunting for the right shot before the actual work even starts.

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@zephyrlink_i That’s such a real part of editing. Finding the right shot can take longer than actually using it, especially when you’re working across years of footage. We want Clipto MCP to handle that search so you can spend more time on the edit itself. Thanks!

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Being able to search across local video and audio throughnatural language could save a ridiculous amount of time

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@eeeeeach That’s a big part of why we built it. The content is already there—the frustrating part is remembering where it lives and going through hours of video or audio to find one moment. With Clipto, you can just describe what you remember and let it find the right part. Thanks YICHI !

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#3
Origin by Cursor
The Git forge built for the age of coding agents
292
一句话介绍:Origin by Cursor 是一个内置于 Cursor 编辑器的代码托管与协作平台,让开发者直接在编辑器内创建和管理 Git 仓库、发起代码评审,并让 AI 编程 Agent 与人类在同一个工作流中协同,解决“Agent 写代码但评审和托管流程仍停留在旧范式”的痛点。
Developer Tools Artificial Intelligence
代码托管 Git 仓库 AI Agent 协作 代码评审 拉取请求 开发者工具 集成开发环境 版本控制 持续部署 Cursor
用户评论摘要:用户普遍认为产品时机精准,尤其是 GitHub 宕机后更显价值。核心关注点集中在:Agent 提交 PR 后是否仍需人工审批;与 GitHub 的 stacked PR 功能相比有何差异;以及希望接入 Appwrite 等自动部署服务,优化 Agent 代码从评审到上线的路径。
AI 锐评

Origin 的野心不止于做一个“编辑器里的 Git 客户端”,而是试图定义“Agent 优先”的代码协作范式。从评论看,用户真正焦虑的不是“能不能存代码”,而是“当 Agent 写了 80% 的代码后,评审和部署环节如何不被人类拖后腿”。Origin 把仓库从 GitHub 挪进 Cursor,本质上是把 AI 从“辅助写码的工具”升级为“开发流程的一等公民”——这比单纯加几个 Agent 快捷键要激进得多。

但风险同样明显:其一,绑定 Cursor 生态意味着它天然拒绝多 IDE 和多元工具链,这在企业级落地时会遇到阻力;其二,用户对“Agent 提交的 PR 是否绕过人工审批”的追问,暴露出责任归属和代码安全性的模糊地带——如果 AI 生成的代码自动上线出了问题,谁来兜底?Origin 目前并未给出机制性回答。

此外,GitHub 自身已在推进 Copilot 深度集成和 stacked PR,Origin 若不能在 Agent 原生能力(如自动整理提交、智能合并冲突、基于意图的评审队列)上形成代差,就容易被巨头裹挟。真正的价值在于抢占“人机协作开发”的入口标准,但这条路需要更清晰的信任模型和开放的生态姿势,否则容易沦为 Cursor 重度用户的“高级插件”。

查看原始信息
Origin by Cursor
Origin is Cursor's new code hosting platform, built for a world where humans and coding agents work side by side. Create and host Git repos directly in Cursor, browse and search code, open and review pull requests, manage access, and sync with GitHub. Your code now lives next to the agents working on it—with more agent-native features on the way.

Excited to see this launch, team! Definitely arrives at a necessary time.

We're working on an integration to allow automatic deployments of sites and functions on Appwrite from Origin, would love to connect with any relevant engineering/DevRel team members about the same.

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@aditya_oberai an Appwrite integration here is the piece I have been waiting for. One question it raises: when an agent opens the pull request, does the deploy still wait for a human approval, or does agent-authored code get the same automatic path as mine? That distinction starts to matter once agents are opening most of the PRs.

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Can't wait to test it!

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Really cool. Congrats on the launch, Justin. Most of what my team ships internally is agent-written now and the review step is the part that hasn't caught up, so that's where I'll be testing this.

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@GitHub down earlier this week, the timing is perfect.

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Love the new beta stacked feature in github, as long as you dont need to rebase :D. How does this stacked feature in the new cursor origin compare?

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I'm now a daily user of github stacked PRs feature, excited to try this.

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Eleven launches in and you are still taking the hard route. Congrats on building a whole Git forge instead of another editor feature. That is a lot of work for a company that could coast.

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My entire codebase is now officially cursor-native: cursor + grok-bot + origin and bugbot

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Love that Origin puts the repo right next to the agents working on it instead of treating agent workflows as an afterthought bolted onto a human-first forge.

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#4
Claude Watermark Remover
Find and remove every trace AI leaves in your text
221
一句话介绍:Claude Watermark Remover 是一款在浏览器本地运行的文本检测与清理工具,帮助用户精准找出并一键移除从 AI 聊天界面复制文本时残留的隐藏 HTML 类名、零宽字符及特殊排版痕迹,解决“复制粘贴带毒”的痛点,且免费不限量、无需上传。
Writing Privacy Artificial Intelligence GitHub
AI文本检测 水印移除 文本清理工具 零宽字符 隐私保护 浏览器本地运行 开源软件 开发者工具 内容创作辅助 Product Hunt
用户评论摘要:用户主要质疑产品名称有“标题党”嫌疑,因开发者自认无法检测Anthropic统计水印,却用“Claude水印移除”命名,易误导新手。部分用户认同“无需检测即可通过改写法移除”的思路,开发者回应称重写步骤可打破措辞模式,但承认无法100%验证。另有用户提醒“Claude”商标存在下架风险,以及指出破折号作为AI信号并不可靠,开发者对此表示认同。
AI 锐评

这款产品的诚实堪称业界清流,但这份诚实也恰好是它最大的商业悖论。开发者用“无法检测Anthropic统计水印”的直白声明,亲手拆掉了“Claude Watermark Remover”这个名字的合法性根基——你已经承认自己做不到核心承诺,却依然用“Claude”和“Watermark Remover”作为引流招牌,这不仅是评论中用户指出的“误导”,更是一种自我设限的营销失误。从技术价值看,它能精确计数并定位复制粘贴产生的隐形字符,确实解决了“所见非所得”的真实痛点,且开源、本地运行、无限免费,对技术敏感型用户有极强吸引力。但产品的深层问题在于:它把“事实”与“价值”混为一谈。能指出零宽字符是事实,但用户要的是“我的文本是否看起来像AI写的”这个概率判断。你提供的事实越精确,对普通用户就越没用——他们不在乎字节,只在乎安全。评论区里关于“重写模式”的讨论才是真正的产品方向:与其做显微镜,不如做过滤器。开发者若能把“客观检测+去痕+重写去模式”打包成一个完整的“AI痕迹净化器”,并弱化对“Claude”的碰瓷依赖,价值会陡增。目前这版更像一个专业向的“文本法医工具”,赚了口碑,但离“水印移除”的刚需市场还很远。顺带一提,商标风险是悬在头上的一把刀,改名是迟早的事。

查看原始信息
Claude Watermark Remover
Paste any text and see every trace a chat interface left in it: hidden HTML class names, zero-width characters, exotic spaces, typography. Each finding has a count and a position, because these are facts about the bytes, not a probability score. Clean it in one click. Free, unlimited, no account, runs in your browser so nothing is uploaded. It does not claim to detect Anthropic's statistical watermark, because nobody outside Anthropic can. The engine is MIT open source.

Hey Product Hunt 👋 I built this after the Claude watermark news in August, when the internet filled up with tools promising to remove a watermark nobody outside Anthropic can actually detect. This does the part that is real. Copying out of a chat interface carries things with it: HTML class names, zero-width characters, exotic spaces, typography. Paste anything and you get every one of them with a count and a position, because those are facts about the bytes rather than a probability score. One click strips them. Two things I would rather say up front than bury. First, it does NOT detect Anthropic's statistical watermark. Nobody outside Anthropic can, because verification needs a key that has not been released. Any tool claiming otherwise is guessing. Second, the em dash is not the tell people think it is. I ran ten pre-computer novels through the checker: Melville uses 26 per thousand words in Moby Dick, while Austen and Stoker use none at all. A signal that swings from 0 to 26 across human authors cannot accuse anyone of anything. The detection engine is MIT open source, so you can check both of those claims instead of trusting me. Free and unlimited to check, runs in your browser, nothing uploaded. I would genuinely like to hear where it gets things wrong.

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@ofir_smolinsky 
Misleading. In your intro you make the honest statement that nobody can detect what Anthropic is doing yet. Since you know this, using "Claude Watermark Remover" is, at best misleading and will give newbie people who don't read this chat, will just click to your site and see the words "every trace" which is also misleading and false. You do the work to build something then damage your creditability with this clickbait-type prose. Not cool.

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Cool approach, and agreed that you can't detect Anthropic's watermark without their keys. But on removal I wouldn't fully agree: you don't need to detect a watermark to remove it. There's research showing these watermarks mostly don't survive paraphrasing or translating back and forth.

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@florian_luttgenau yea exactly, thats basically why i added the rewrite step 😄 the free cleaner removes the literal copy paste artifacts, then the optional rewrite runs it through a different model to break up the wording patterns. i still wouldnt claim the watermark is 100% gone cuz theres no way to actually verify that without anthropic’s key, but yea on the actual removal approach we agree

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You can't use "Claude" in the name, ban incoming.

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This is such a great response to their updates :D

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@busmark_w_nika thank you :) the update created a lot of panic and a lot of tools claiming certainty they don’t have. i wanted to build the verifiable version: show what’s actually in the text, clean it, and be honest about what nobody outside Anthropic can currently prove.

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You ran ten pre-computer novels through the checker to test the em dash theory. Moby Dick hits twenty-six per thousand words, Austen none. Congrats on shipping something that leads with what it can't do.

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@lucasjpols appreciate that. honestly the em dash rabbit hole was one of the reasons i shipped it. people were treating typography like proof of AI, while old books show how weak that claim is. i’d rather lead with the limitation than sell fake certainty.

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I don't see any issue with cloud watermarking, but anyway, good niche findings! Good luck!

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@maksym_shcherbakov1 yea i dont really have an issue with claude watermarking either lol. my issue is more with tools claiming “100% removed” when they literally cant verify that :) this just shows whats actually there, cleans it, and lets u rewrite the wording too if u wanna go further. appreciate u checking it out

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#5
Hosted Agents in Cluing
Collaborative agents who build, learn and publish in 1 place
180
一句话介绍:Cluing Hosted Agents 将AI智能体从个人电脑搬到云端协作空间,让非技术团队无需配置即可创建、共享、跨设备管理能持续学习并自主发布成果的AI员工,解决智能体“只能跑在个人电脑上、无法团队协作”的核心痛点。
Android Productivity Artificial Intelligence
AI智能体托管 团队协作 无代码自动化 AI工作流 知识管理 自定义连接器 移动端管理 MCP协议 SaaS工具
用户评论摘要:用户普遍认可“免配置、云端托管、团队共享”的价值;创始人回应了痛点:此前需保持电脑开机、猫会踩关机、内存崩溃、多智能体互相干扰等问题。用户好奇其最亮眼的端到端工作流案例(获回复:自动内容规划、连接GA/GSC生成实时仪表盘)。有用户表示将试用,整体反馈积极,无重大负面意见。
AI 锐评

Cluing的这次发布,本质上是对“AI智能体”这一概念的一次祛魅和落地。当前市场充斥着一堆跑在开发者终端里的半成品Agent,它们把“高门槛”误认为“高价值”。Cluing聪明地将战场从IDE编辑器转移到云端共享工作区,直击了企业采用AI的真实阻力——不是模型不够聪明,而是流程无法嵌入组织。

其核心护城河并非模型能力,而是“团队资产化”这个定位。将智能体从个人玩具变为团队可交接、可审计、可积累知识的公共资源,这比单纯提供“托管”服务高明得多。自动构建连接器(及内置MCP支持)和技能与知识库同步,是直击规模化痛点的设计;而移动端管理、猫踩关机这类接地气的叙事,则精准击中了早期采用者与实用主义者的情绪。

但必须泼一盆冷水:180票的成绩在PH平台并不亮眼,说明该赛道已相当拥挤。Cluing面临的最大问题并非功能,而是生态位。前有Zapier这类“无代码自动化”巨头凭借海量集成向下兼容,后有各大云厂商将Agents作为云原生基础能力免费捆绑。Cluing若不能在细分行业(如营销、运营)沉淀出不可替代的垂直工作流模板,很容易沦为“听起来很美”的通用工具。此外,将并发、状态管理、知识库同步全部托管,其背后的成本结构是否健康、能否支撑免费额度后的续费转化,都是需要时间验证的生存问题。总之,方向正确,但能否在巨头的阴影下活出规模,尚需观望。

查看原始信息
Hosted Agents in Cluing
Cluing Hosted Agents take agents off one person’s laptop and into a collaborative workspace. Start work from your computer, continue on your phone, and hand it over to teammates without losing context. Evolving skills update as you collect new insights and agents become a team asset. Anyone can now assign tasks, publish their work, and connect to any external tool with an API or MCP with Cluing's custom connectors. Close the laptop - the work will keep going.

As a former marketer, I loved the benefits of AI agents, but hated the complex setup and the fact that my second brain needed extra steps to be plugged in.

So we decided to change that with Cluing.

Cluing agents are fully hosted with us, require no technical setup, and learn right alongside you. Custom connectors make sure whatever your tech stack is, we've got you covered.

You can even take us with you and manage agents straight from your phone.

Can't wait to hear your thoughts 💛

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@sandra_idjoski Best of luck with the launch :)

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@sandra_idjoski This is amazing! Love to see all the moves and the direction of @Cluing , I hear all the time how people want to setup an agent, but don't know where to get started, or what to do with it. Wishing you and the team all the best!!! This is truly an amazing step forward.

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@sandra_idjoski congrats on your launch today! Keep the good work and see you around.
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Hey Product Hunters, miss us? 😄

We just launched Autonomous Agents in Cluing - Claude Code capabilities, hosted and shared across your team! I've spent the last few weeks basically living inside these agents, so I'm genuinely thrilled they're finally out. 🎊

A few things I love about them:

🧠They already know your context - your knowledge and past work live in the same workspace.

🔌 If a connector doesn't exist, the agent just builds one (and stores your credentials securely).

⚒️ Skills stay in sync with your Topics, so your whole team stays aligned without rewriting prompts.

🌐 They can publish a page or app live, right from Cluing - even on your own domain.

👥 And they live in a shared workspace, so your team works with the agent, not around it.

Best part for a non-developer like me: if you can describe a task, you can run an agent for it 😄

I'll be around all day and would genuinely love to hear what you'd connect an agent to first. Ask me anything! 💚

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Long time no see makers! Tech Founder here 👋

The idea for hosted agents came from our team, we were using different harnesses and automating our work but:

➜ The mac needed to stay open - Cats would also shut down our agents

➜ Real collaboration was almost impossible

➜ I spent a ton of time just keeping everything up and running

➜ No true isolation - All agents same machine, running 15 chrome instances eating up the RAM, disrupting one another

➜ And the thing that drove me nuts - Sessions handling was on a harness level - Every new comment would reread things again and again, hallucinate mid-work..

So we started with our own hosted agents inside our team, the Cluing memory was natively already there, after we got a ton of value out of it, we decided to make it a part of the product for everyone.

There's a 25% OFF all seats, there's $25 Free Credits ($300 for yearly subs) for every new subscription, give it a try!

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@ralic congrats on the launch!

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Very exciting, congrats on the launch!

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Thank you @farbodsaraf!

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@farbodsaraf thanks mate!

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@ralic @gordana_laskovic @nemanja_trtica congratulations on the launch!

Really like the direction here. Moving agents from something that lives on one person’s laptop to something the whole team can actually collaborate around feels like a big unlock.

Curious, what’s the most impressive end-to-end workflow you’ve already seen a team hand over to a Hosted Agent? Would love to hear what it can do in the wild.

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My favourite one was handing over content planning to an agent hooked up to all the marketing analytics.

Tracks what you're bookmarking, reading, and saving and uses that to fill out the content calendar each month. Plus, keeps an eye on what's ranking well on Google and what the trending topics in the industry are.

The agent built the connector, monitors the topics, matches the team's voice, and fills out the calendar monthly with no legwork from the team.

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@rizzykicks  Thanks! One of the coolest workflows I've built so far was connecting Google Search Console, Google Analytics, and Ghost and having the agent turn everything into a live dashboard with the data. It's pretty cool to see the whole thing running end-to-end without having to touch the terminal

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congrats team 🎉 the no-setup part is what makes this click for me. rooting for you

2
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@ashimanski thanks Artyom! Glad to hear that 😄
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Needed a solution for my current problem. I’ll be trying it out. Congrats on the launch!

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Thank you@vignestion!

Ping us if you need any help setting up.

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Cats kept shutting down your agents on the old setup. That's the most honest reason to host anything I've read today. Congrats on the eighth launch, four years in and still writing like people.

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Thank you, @lucasjpols , we do our best 😄

The anxiety of not being able to check up on the agents also played a big role in making them available in our apps 😅

0
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#6
Paper Critters
Kid friendly paper toys, free to decorate and COPPA safe.
127
一句话介绍:Paper Critters 是一款免安装的儿童纸玩具设计PWA,让孩子在线用贴纸自由设计角色并打印折纸,兼顾屏幕创意与动手乐趣,且无需账号邮箱、COPPA合规。
Kids Toys Family
儿童创意 纸玩具 打印手工 渐进式网页应用 COPPA安全 无需账号 贴纸设计 家庭亲子 教育工具 免安装
用户评论摘要:用户赞赏其“无账号、无邮箱、人工审核画廊”在儿童软件中尤为难得;创始人自述期待贴纸装饰控件及打印组装体验的反馈。目前评论量少,有效建议集中于交互细节和实体制作流程的优化空间。
AI 锐评

Paper Critters 的聪明之处在于它没有试图对抗“屏幕时间”,而是将其转化为物理世界的入口。核心价值绝非“在线贴纸”,而是“打印即转化”——它把数字创作的虚拟成就感,通过一张A4纸和剪刀胶水,落成可触摸的实体玩具。这对家长而言,是“屏幕时间产出实物”的罕见叙事,极具付费说服力。

从产品策略看,其克制是最大亮点:无账号、无邮箱、人工审核画廊,直接切中欧美家庭与学校对COPPA的极度敏感。这比任何花哨的AI功能都更本质——它卖的是“安全使用的权利”。PWA的形态也精准,省去应用商店下载障碍,符合儿童工具“即开即用”的低摩擦预期。

但隐忧同样明显。其一,商业模式依赖“一次性付费打印高清模板”,而家长完全可以用截图+免费PDF工具绕过付费,需思考如何将价值锚定在“打印质量+拼装体验”之外(如独特IP或进阶模板库)。其二,人工审核画廊虽安全,却难规模化,一旦用户量上升,审核成本将成为沉重负担,需探索AI预审+人工抽检的混合机制。其三,产品功能单薄,贴纸装饰若缺乏足够丰富的素材库和创作深度,儿童新鲜感消退极快,留存堪忧。

总体而言,这是一款定位精准、伦理正确的“小而美”产品,但要想从玩具变成可持续的生意,必须在内容生态(持续更新贴纸、主题包)和社区机制(鼓励孩子分享实体作品回传照片)上做二次创新。否则,它很可能沦为“一个很棒的公益项目”,而非一门好生意。

查看原始信息
Paper Critters
Paper Critters bridges digital creativity with hands-on play. Kids design custom paper toy characters online using full sticker controls, then print them as ready-to-assemble crafts with built-in cut and fold lines. Fully responsive across mobile, tablet, and desktop, this PWA installs to the home screen with no app store download required. It is free to start, kid-safe by design with no account or email required, and features a moderated gallery alongside private saving.

Hey Product Hunt! 👋

I am J.R., creator of Paper Critters.

Paper Critters lets kids design custom paper toy characters using full sticker controls, then print and fold them into real physical toys. It bridges screen time with hands-on play, making it a great creative outlet for kids, parents, and educators.

Key features to check out:

  • Kid-Safe Privacy: No email collected, no account required to try, and built around child privacy constraints from day one

  • Frictionless Web App: Fully responsive Progressive Web App that installs to your home screen with no app store download required

  • Safety First: Human moderation on all public gallery submissions

  • Monetization: Free to design and explore, with a simple one-time purchase to print high resolution templates with cut and fold lines

I would love your feedback, especially around the sticker decoration controls and the overall print-to-assembly experience.

Thanks for checking it out! 🎨

4
回复

@jrfab650 Congrats! No account, no email, human-moderated gallery in kids' software is the feature.

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Super cool toy for kids! Love this

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@zeng Thank you :). I appreciate the support.

0
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#7
Expert Chase 2.0
Where human life runs with AI
127
一句话介绍:Expert Chase 2.0是一款集成了AI对话、日程提醒与生活任务管理的智能助手,通过自然语言指令在手机、网页等多端帮助用户高效管理日常琐事,解决“记不住、易遗漏”的生活痛点。
Productivity Artificial Intelligence Lifestyle
AI生活助手 智能提醒 日程管理 任务管理 多端同步 自然语言交互 效率工具 健康管理 生活服务 移动应用
用户评论摘要:用户整体反馈积极,称赞界面设计简洁、桌面与移动端体验统一。核心有效提问集中在:如何吸引仍习惯传统纸质/手动记录方式的用户?开发者需明确目标人群定位与差异化获客策略。另有用户表示支持并期待持续迭代。
AI 锐评

Expert Chase 2.0本质上是一个“AI记事本+提醒器”的缝合体,其核心卖点并非革命性技术,而是将语音/文字指令转化为结构化提醒的低摩擦交互。从评论看,产品完成度尚可,但“让日常生活更简单”是极度拥挤的赛道——前有系统原生提醒(如Siri、Google Assistant),后有Notion、Todoist等深度工具,甚至微信文件传输助手都能替代其基本功能。真正的价值在于“多端一致性和场景整合”,但若缺乏独特数据闭环(如健康数据联动、社交协作)或本地化AI模型优势,极易沦为短命的“轻量工具”。开发者自称“2.0是脑中原版”,暗示1.0用户留存不足,而评论中无人追问技术细节或数据安全,说明用户对AI能力并不敏感,更关注体验流畅度。若想突围,建议瞄准“数字断连人群”或“中老年管家场景”,用极简交互+强提醒渗透率换取粘性,而非与效率工具正面竞争。当前版本更像一次“优雅的修修补补”,距离“Where human life runs with AI”的宏大叙事仍有本质差距。

查看原始信息
Expert Chase 2.0
A completely redesigned experience, built to make everyday life feel simpler, more connected, and more useful. Open it. Explore it. Experience it yourself.

Thanks for using Expert Chase.
Version 2.0, first wave of the redesigned UI

• Reminders from chat on device. Say “remind me to call Mom at 3,” “remind me 30 minutes before my meeting,” “remind me every morning to take vitamins,” or “remind me to drink water.” Works for tasks, events, habits, or a wellness check-in
• Refined Explore and glass-style navigation in the app
• Faster, more reliable everyday interactions
• Quicker inline compose when you add something new
• Stability and performance improvements
• Squashed some bugs along the way

We’re glad you’re with us.


I’ve been building Expert Chase for a while, and 2.0 feels like the version I originally had in my head.

This isn’t just a feature update. I redesigned the experience from the ground up and brought together the parts of everyday life you need in one place.

I’d love for you to try it and tell me what you think.

Expert Chase 2.0 is now live on iOS, Android, and Web.

Download on the App Store:

https://apps.apple.com/us/app/expert-chase-ai-for-life/id6766313000


Get it on Google Play:
https://play.google.com/store/apps/details?id=com.expertchase.app

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回复

Looks amazing, congrats on your launch @eye 🚀

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really interesting idea! curious how you hope to capture users who are currently operating in a more - analog capacity to this? Or is that even part of the prospective demo?

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The redesign looks really clean, especially the way the desktop and mobile experience come together. The idea of making everyday life feel simpler and more connected is interesting. Congrats on the launch!
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Happy to see you re-launching :)

0
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@busmark_w_nika Thanks Nika!

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@eye Congratulations. And happy product launch.

0
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@huisong_li Thanks Huisong!

1
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#8
Fairphone Gen 6+
A modular phone built to last through 2033
125
一句话介绍:Fairphone Gen 6+ 是一款主打模块化拆卸与自主维修的 5G 手机,面向长期使用主义者,解决“手机不耐用、维修难、被迫频繁换机”的核心痛点,承诺软件支持至 2033 年。
Hardware Cell Phone
模块化手机 可维修设计 5G智能手机 环保科技 长寿命设备 用户自主更换电池 公平贸易电子 美国首发 骁龙7s Gen4 五年质保
用户评论摘要:用户整体认可其维修理念与可换电池设计;最关注首次美国直销的实际市场反响,质疑美国消费者是否像欧洲一样接受可维修性;另有评论感叹少见隐私相关产品,但未具体展开;少数评论仅表达了对换电池便利性的喜爱。
AI 锐评

Fairphone Gen 6+ 的“Plus”本质是一次保守的硬件中期改款,而非创新迭代:换装骁龙 7s Gen 4 与 12GB RAM,只是为了给既有模块化架构续命,而非解决根本体验短板。它真正的价值不在手机本身,而在于商业逻辑——将“维修权”从营销口号变为默认服务,以五年保修和 2033 年软件支持重新定义电子产品的生命周期成本。然而,这一价值能否兑现,取决于两个关键矛盾:其一,硬件平台性能在八年长周期内必然快速落伍,即便电池可换,骁龙 7s 系列的中端定位到 2030 年还能否满足日常应用,令人存疑;其二,模块化设计的可升级性并未覆盖 SoC 与内存,消费者买到的是“可维修的固定配置”,而非“可进化的硬件”。评论中美国市场首销的疑问非常精准——欧洲成功建立在政策补贴与环保消费文化之上,而美国市场规模巨大却极度依赖运营商补贴与以旧换新,Fairphone 的直营模式缺乏渠道支撑,恐难复制欧洲渗透率。更关键的是,用户评论中“隐私”的提及暴露了宣传定位混乱:可维修与隐私并无强关联,如果不能讲清“延长使用即减少数据留痕”的隐含逻辑,这类用户极易流向专业隐私手机品牌。总体而言,这是一款值得尊敬的“正确产品”,但它的长期社会价值远高于对个体用户的当下使用价值;在 AI 换机潮和订阅式手机挤压下,它更像一面旗帜,而非一种主流答案。

查看原始信息
Fairphone Gen 6+
Meet Fairphone Gen 6+, a repairable 5G smartphone with a five-year warranty, replaceable parts, a 50MP camera, and support through 2033.

Hi everyone!

One of my favorite @Fairphone details is still the screwdriver in the box. You’re actually expected to open the phone!

The 6+ keeps the same repairable chassis with 12 user-replaceable parts, a removable battery, a five-year warranty, and software support through 2033. The update is mostly inside: Snapdragon 7s Gen 4 and 12GB of RAM, giving a phone meant to stay around for years a bit more headroom.

The “Plus” is deliberately modest. No bigger display or extra camera. Fairphone has basically taken last year’s 6 and made it more comfortable to age.

And for the first time, Fairphone is selling directly in the US.

A phone that ships with the tool to keep it alive for years is a pretty refreshing idea.

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Thanks for sharing. It's so rare to see privacy related products here.

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Love this idea, my iPhone battery is always dead and here I can just swap it.

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Hey Zac. First direct US sale is the interesting bit. Any read yet on whether repairability actually lands with American buyers the way it has in Europe?
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#9
OmniVibe
Marketplace for agent creators & users
118
一句话介绍:OmniVibe是一个AI代理(Agent)市场与协作平台,让非技术用户通过类似Slack的对话界面按需调用多个专业AI代理,同时让开发者发布并变现自己的代理作品。
Productivity Social Media Artificial Intelligence
AI代理市场 Agent Marketplace 多代理协作 无代码AI 创作者经济 代理分发 SKILL.md 工作流自动化 AI应用商店 模型编排
用户评论摘要:用户普遍认可“让代理走出GitHub”的定位,赞赏Slack式多代理交互对非技术人群友好。核心诉求集中于:1) 发现与信任机制(如何确保代理质量与安全);2) 创作者变现路径的可持续性;3) 简化从本地环境到云端的发布流程。创始人回应承诺优化审核与协作体验。
AI 锐评

OmniVibe踩中了AI应用从“写代码”到“用服务”的必然拐点。其本质不是又一个聊天工具,而是试图成为Agent时代的“App Store + Slack”复合体。从评论看,产品切入的痛点(代理散落于GitHub/SKILL.md,难以触达大众)真实且尖锐,用“聊天式多代理编排”降低使用门槛,方向正确且具备差异化。

但风险同样清晰:首先,市场价值取决于供给侧质量,目前大量Agent仍是套壳API的“玩具”,若审核与评测体系(用户评论中已提及信任问题)跟不上,平台会迅速沦为垃圾场。其次,多代理协作的“后端协调”是极高技术壁垒,OmniVibe目前的Demo仅展示了UI层,若不能解决代理间的上下文共享、任务冲突仲裁和成本控制,所谓的“像Slack一样聊”只是气泡界面下的线性脚本。最后,变现逻辑依赖“按量付费”,但当前Agent的可靠性和复杂任务成功率尚未达到让用户持续付费的临界点。

值得肯定的是,团队没有回避“创作者激励”这一冷启动难题,且创始人对分发痛点有清醒认知。真正的胜负手在于:能否打造一套高质量的“代理质量认证”和“可观测性”体系,让优质代理通过口碑自传播。如果只停留在“聚合链接”层面,OmniVibe很快会被巨头(如OpenAI的GPT Store或微软Copilot生态)的功能覆盖。建议团队将80%精力投入“信任层”建设——包括沙箱安全运行、行为审计和社区声誉系统,这才是长期护城河。目前看,这是一张漂亮的入场券,但距离真正的“代理经济基础设施”还有数个版本迭代的距离。

查看原始信息
OmniVibe
OmniVibe brings specialized AI agents and the people who create them into one place. For creators, OmniVibe gives your agents a place to live beyond your local harness, GitHub repo, or SKILL.md. You can import and publish the agents you already have, then earn from qualified usage. For users, browse or tell OmniVibe what you need. It finds the right agents. Work with multiple agents at once, like messaging your coworkers on Slack. OmniVibe is a home for the agent creator economy.
Hi Product Hunt 👋 We built OmniVibe because we kept seeing talented agent builders create amazing things—but most users never get to experience them. We believe a great agent deserves to live beyond your local harness, a GitHub repo, or a SKILL.md file. It should be discoverable, easy for anyone to use, and able to create value for its creator. That’s why we built OmniVibe: an agent marketplace where you can discover specialized agents, collaborate with them in one workspace, or create and publish your own. FOR USERS Simply tell OmniVibe what you want to accomplish. It finds the right agents and coordinates the workflow. You can work with multiple agents at once, just like messaging your coworkers on Slack. FOR CREATORS Studio helps turn an idea into a working agent. You can refine it, publish it through one link, share it with your audiences, track its usage, and earn when people use your creation. We’re still early, and we’d love to learn from this community: 1. Do you have any local skills or agents you’re eager to share—but haven’t found a good way to distribute? 2. Would you use a marketplace that makes it easy to publish your agents and earn when others use them? 3. What’s the biggest blocker stopping you from publishing and sharing your agents today? Thanks for checking us out. We’ll be here throughout the launch and would love to hear what you think about our product!!! 🚀
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@alex_luan looking forward!

1
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@alex_luan 

Congrats on the launch! The site experience actually does a great job of what most AI tools get wrong, you land and immediately understand what it is, who it's for, and what you can do.

The agent categories are well organized and the "just like messaging your coworkers on Slack" framing for multi-agent collaboration is a smart way to make an abstract concept feel familiar.

The Creator Program angle is interesting too turning builders into earners is a strong retention hook.

Rooting for this one🎉

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We don't have a support team and all - we don't know if this post will be ignored among other launches.

But, for everyone that does land on this page - We will treat EVERY. SINGLE. ONE of your comments with FULL hearts.

Please let us know what you think, it'll be a pleasure.

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deploying agents are very difficult for non-technical people, really appreciate omnivibe to make using agents more friendly to us

2
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@audrey_zhou That's true pain point now! We are trying to make agentic skills just like mobile app that just works out of box which doesn't require any background in tech, for most people!

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The Slack-like messaging approach for chatting with multiple agents is my favorite. Congrats team! 👏

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@jurgen_pergega That's definitely one of our key differentiator! :) Omnivibe can help coordinate the tasks in the back end among your agent "coworkers" in the group chat.

The goal is to make the experience as natural as possible!

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There are so many cool agents buried in GitHub repos that most people will never find. I can see the appeal here. Congrats!

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@henry_habib Thank you for your support!! Feel free to onboard your cool skills on our platform :) We have a good numbers of users already even before launch. And we want to make sure the Creators are getting paid for their skills!

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Really like the idea of giving AI agents a place beyond scattered GitHub repos and local setups. Making them easier to discover, use, and even monetize feels like a natural next step for the agent ecosystem. Congrats on the launch!

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@better_shaya thanks Shaya! We are going to continue to optimize our onboarding flow to unblock creator’s creativity. I.e. transform any their local workflow from local harness to cloud and used by others!

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I appreciate that the product does not assume every user knows what a SKILL.md file is. The best agent experience should feel like using a product, not configuring a developer tool.

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@wenjun_shi Exactly. SKILL.md should be useful for creators, but invisible to users. Users should just say what they need and get the right agent.

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This is huge, congratulations on the launch! I know @lotus_lu1 personally and she is a GTM guru. If some other teams building an agent marketplace product, I will be suspicious about the distribution. With Lotus leading the GTM, I am sure OmniVibe has a high chance to success.

Keep going!

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@renchu_song Thank you Richard for your support & kind words!! Let's stay in touch!

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The biggest blocker for me is discoverability and trust, knowing people will actually find it and that it's safe to use. A marketplace with good curation would solve both.

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@lvyanghuang Totally agree. Finding an agent is only useful if you can trust it. We want to make both easier, and curation will be a big part of that.

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#10
Cronloop AI
AI agents that run in a loop
112
一句话介绍:Cronloop AI 让用户用Markdown描述任务,按固定频率(5分钟至每周)循环运行AI代理(支持Claude Code/Codex),自动完成重复性工作,无需人工干预。
SaaS Software Engineering Artificial Intelligence
AI代理循环调度 定时自动化 Claude Code集成 无代码工作流 AI记忆系统 沙箱执行 自优化代理 开发者工具 MCP连接器 订阅制SaaS
用户评论摘要:用户认可“临时沙箱+持久Markdown记忆”的设计,并好奇多代理并发时如何管理API速率限制和会话超时;询问免费试用机制及运行间状态保留方式;同时提供实际用例(如自动检查客服工单、SEO优化、事件聚合网站),整体反馈积极。
AI 锐评

Cronloop AI 本质上是一个“定时触发器+LLM代理执行器”的封装,其巧妙之处在于将“循环”和“记忆”作为核心抽象,精准击中了重度AI用户(如用自己的Claude/Codex订阅)的自动化痛点——过去需要自己写cron脚本、维护状态数据库、处理沙箱清理,现在用Markdown指令和记忆文件一步到位。它没有自研模型,而是“榨干”用户自带的推理额度,这既是成本优势(Pro版$25/月无代理数量限制),也是隐性脆弱点:底层依赖Claude Code/Codex的CLI稳定性,一旦上游限流或接口变更,所有代理即刻瘫痪。评论中关于“同订阅多代理并发限流”的提问,开发者并未正面回应,实际上这是架构级风险——用户自带API Key时,多个沙箱同时呼叫同一key极易触发429错误,而产品并未展示智能排队或配额分配机制。此外,“Markdown记忆”虽然轻量易读,但长期运行后会导致上下文膨胀、噪音累积,缺乏遗忘机制或向量检索,所谓的“self-improve”更多是工程师手写提示词的“伪进化”。从商业角度看,产品精准瞄准“想要无人值守自动化但怕锁死生态”的开发者,用自带Key模式降低了迁移成本,但这也意味着它很难从推理用量中抽成,只能靠订阅费+连接器增值。若未来能加入多代理协作编排(如代理间共享记忆的权限控制)和故障自愈(限流自动重试、智能降级),“代理农场”的想象空间才会真正打开。现阶段它更像一个“高级cron+日志面板”,而非智能体操作系统。

查看原始信息
Cronloop AI
Cronloop lets you create AI agents that run in a loop, from every five minutes to once a week. Just describe the job in plain Markdown, pick Codex or Claude Code, connect your tools, and you're done. Every agent has a durable memory system and can self-improve each run. Create your first agent for free today.

Hey PH,

I often want to automate recurring tasks with my Claude Code/Codex subscriptions, so I built Cronloop to make this simple.

Just click "New agent", set a schedule, connect your existing claude code/codex subscription, give your agent instructions, connect the tools it needs, and boom - you have an autonomous agent running in a loop, working while you sleep.

Some ways I'm using it:

- I built a self-driving events website (aievents.now) and have a cronloop agent for each city that autonomously curates events every morning.
- I have a few websites autonomously SEO-optimizing every day based with connected search console data + keyword research tools - the site runs on Cactal.ai.

Some features:

- Every agent runs in an ephemeral, isolated sandbox
- You can monitor runs in real-time (the agent logs stream into the app)
- Every agent has a simple, durable markdown-based memory system. Your agents can self-improve over time - you can include instructions to record learnings with each run for other agents to benefit from.
- You can leverage your existing claude code/codex subscriptions or bring your own API key.
- 200+ connectors are ready-to-go - connect your agents to any tool that has an MCP, CLI, SDK, API, etc.
- You can configure the agent's environment with a setup shell script if needed for greater flexibility

Free to try - create up to three agents for free.

You bring your own inference, so cronloop is very generous with usage, the pro plan offers unlimited agents with up to a 5 min interval on runs for $25/mo (or $20/mo annual).

I'm a huge Cronloop user and get a lot of value from it (I personally have ~25 cronloop agents running), so I'm excited to share it. Let me know your thoughts!

*Hand-written comment, no AI

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@mike_tromba is there a free trial for this? Would love to try before deciding on subscribing.

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@mike_tromba How do you handle state persistence between runs?

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@mike_tromba Congratulations on the launch! As someone who manages around 25 agents myself, it’s clear this was created out of genuine personal need.

The combination of an ephemeral sandbox with durable markdown memory is really smart. It perfectly balances keeping things clean and isolated while allowing agents to build context and learn over time without the burden of a heavy database. Plus, using existing Claude Code/Codex subscriptions is a fantastic way to keep inference costs manageable.

I have a couple of quick questions:

How are you managing rate limits or session timeouts when multiple scheduled agents are hitting the same subscription/API key at the same time?

Regarding the setup shell script in the sandbox, do you cache environment states across runs for speed, or does it start fresh from scratch every single time?

The self-driving events site and Cactal.ai SEO loops are impressive real-world examples. I’m definitely going to pick this up to automate some of my daily development workflows!

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This looks cool for checking support tickets every day. Agents that run by themselfs is a good idea.
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@This @priyankamandal Thank you Priyanka! Yes, this is a good use-case for an agent loop. You can connect it to your support ticketing, CRM, etc. and have it continually check for new messages and respond however you'd like.

0
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#11
ChatGPT for Teens
ChatGPT, built differently for teens
105
一句话介绍:ChatGPT for Teens 是一款专为13-17岁青少年重造的ChatGPT,通过“学习模式+测验+可视化”替代直接给答案,解决青少年用AI抄作业、过度依赖以及家长担忧安全隐私的核心痛点。
Education Artificial Intelligence
青少年AI助手 AI学习工具 教育科技 防作弊机制 家长控制 隐私保护 健康使用 学习模式 测验 内容安全
用户评论摘要:多数用户赞赏“不直接给答案”的定位,认为比普通ChatGPT更适合孩子。主要建议:①希望增加学科覆盖(如数学手写识别);②家长控制面板可更精细(按学科/时段);③部分用户反映“Study Hours”提醒易被忽略,希望强制锁屏;④有人质疑“隐私+家长监控”的平衡,要求明确数据边界。
AI 锐评

这产品本质是OpenAI对“教育场景”的一次防守性卡位,而非进攻性创新。其核心价值不在“AI能力”——那与主版ChatGPT无异——而在“交互约束层”:通过交互设计(先引导思考再给提示)、功能封禁(屏蔽直接答案)、时间管理(Study Hours)来对抗AI的“认知卸载”副作用。这切中了家长最深层的焦虑:不是怕孩子用AI,而是怕AI替孩子思考。

但有两个隐患:其一,13-17岁用户是“破解高手”,任何软性约束(如Study Mode)都可能被绕过,若缺乏设备级强制(如与iOS/Android屏幕时间联动),健康使用只是空谈;其二,“对话私密+家长可查”是一对结构性矛盾——青少年的隐私诉求是刚需,一旦家长控制被感知为“监工”,产品会被抵触,反而把用户推回普通ChatGPT。

商业上,投票数105(约等于5个用户团队)说明热度一般,且OpenAI未公开该产品是否付费。若免费,它只是主版的“分流器”;若收费,则需证明“防作弊+学习脚手架”的差异化价值用户愿意买单。真正的护城河不在功能,而在内容生态——是否能内置可汗学院级的学习图谱和分科题库,否则Quiz和Study Hours只是玩具。最后提醒:AI教育产品最忌讳“既要又要”,与其做大而全的“学习伴侣”,不如先把“数学解题引导”做到闭环,这是当前最强的刚需。

查看原始信息
ChatGPT for Teens
ChatGPT for Teens is a dedicated ChatGPT experience for ages 13–17, designed around how teens learn and use AI. It encourages working through problems instead of simply giving homework answers, with Study Mode, quizzes, learning visualizations, and Study Hours. Stronger safety protections and healthy-use features are built in by default, with optional parental controls—while keeping teens' conversations private.
#12
Mochi
A tiny animated cat for every browser tab.
103
一句话介绍:Mochi 是一款在浏览器标签页上放置迷你动画小猫的扩展,解决用户长时间浏览网页时界面枯燥、缺乏陪伴感的小情绪痛点,提供轻量、无打扰的视觉慰藉。
Chrome Extensions Productivity Open Source GitHub
浏览器扩展 桌面宠物 动画小猫 休闲娱乐 个性化定制 轻量工具 本地运行 无追踪 Chromium插件 情绪陪伴
用户评论摘要:用户认可其可爱趣味性,核心建议是降低非技术用户安装门槛,希望支持多浏览器一键安装。开发者回应已更新安装演示视频、添加图文指南,并确认兼容Edge、Brave等Chromium系浏览器。无其他负面反馈。
AI 锐评

Mochi 的聪明之处在于精准捕捉了“浏览器标签页”这一高频却常被忽视的碎片化场景,并用“低存在感”的宠物陪伴填补了工具理性之外的感性空白。它刻意与“生产力”“通知”“追踪”划清界限,这既是差异化定位,也是生存策略——在Chrome插件生态日益严苛的隐私审查下,“零数据、纯本地”是极具安全感的卖点。但从产品本质看,它是一款典型的长尾情绪消费品,核心价值不在于功能,而在于“可爱经济学”带来的瞬时愉悦和心理锚点。其增长瓶颈也显而易见:20个静态风格缺乏UGC生态,难以形成持续新鲜感;依赖手动拖拽和跨标签记忆,虽有巧思,却未触及更深的浏览器交互惯性。开发者对安装门槛的迅速响应值得肯定,但仅靠GitHub分发和手动加载,根本无法触达主流“非技术玩家”。Mochi真正的机会在于:要么极简化为一键安装的商店正规军,要么深入探索“宠物与网页互动”(如点击小猫触发小动画、陪伴计时),否则它大概率会沦为小众极客的短暂玩具,而非破圈的现象级产品。可爱的确能换来投票,但留住用户需要更扎实的“习惯钩子”。

查看原始信息
Mochi
Mochi lets you place a tiny animated cat companion directly on your browser tabs, like a little friend hanging out while you browse. Pick from 20 local cat styles, drag Mochi anywhere, and keep the same cat in the same spot across tabs. It’s intentionally small and quiet, not a productivity tool, tracker, or notification machine. No accounts, analytics, ads, or remote data. Just a little cat for your tabs :3
I made Mochi because browser tabs can feel a little too empty after a long day. It started as a small side project: one animated cat, then a few more, and eventually 20 different personalities. Mochi stays in the same spot across tabs, can be dragged anywhere, and works locally without accounts, analytics, or extra noise. I’d love to know which cat becomes your favorite, and whether you’d actually keep one around while browsing :3
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Cute fun idea! It would be really cool if it would be an easy to install extension for different browsers (for non-techy people like myself).

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@mad94 Thank you so much!! I’m glad you like Mochi, and thanks for pointing out that the installation should be easier for nontechnical users.

I’ve updated the Product Hunt video to show the complete installation process, and added a step by step guide with pictures to the GitHub repository.

Mochi should also work on Chromium based browsers like Edge, Brave, Vivaldi, and Opera, not just Chrome :3

If you use a different browser, feel free to send me a message here or email me at koustavdatascience@gmail.com. Let me know which browser you use and I’ll check it out. Mochi might be ready to make some new browser friends!!

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#13
Edgemetry
Privacy-first web analytics on Cloudflare's free tier
101
一句话介绍:
Analytics Marketing Privacy GitHub
用户评论摘要:
AI 锐评
查看原始信息
Edgemetry
Edgemetry is web analytics you run yourself: one Cloudflare Worker, one D1 database, no cookies and no consent banner. Deploy in one click, add a 2.1 KB script, and keep unlimited history on the free tier, roughly 20,000 visits a day at zero cost.
Hey Product Hunt 👋 I wanted analytics for my side projects and every option annoyed me. Google Analytics is overkill and drags a consent banner along. Plausible Cloud is a recurring bill for a site with 400 visitors. Self-hosting Plausible means a VPS running Docker, which is more infrastructure than a personal site deserves. So Edgemetry runs on one Cloudflare Worker and one D1 database. Click deploy, point a subdomain at it, paste a 2.1 KB script tag. No API token, no server, no cookie. The interesting part was making it actually fit the free tier. D1 allows 100,000 row writes a day, and DELETE costs the same as INSERT, so the obvious design (one events table, nightly cleanup) burns four writes per pageview and dies at 8,000 visits. Instead, raw events land in per-hour tables with no indexes at all (one write per pageview), and those tables are never deleted from, they're rolled up and then DROPped, because DROP TABLE is DDL and costs nothing. That lands at ~1.2 writes per pageview, and roughly 20,000 visits a day inside the free tier. What you get: five metrics with sparklines and period comparison, stackable filters where clicking any row narrows every panel at once, a choropleth served from your own Worker, realtime, custom events, ⌘K search, multiple sites and viewer accounts. No third-party request from any browser, ever. The demo is the real dashboard on made-up traffic, no sign-in: https://hayaran.github.io/Edgeme... Happy to answer anything, especially about the D1 cost model or where it breaks.
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@nitinhayaran 

Congrats on the launch! Self-hosting real analytics inside Cloudflare's free tier is the kind of constraint-driven engineering I love (the hourly-table trick to dodge the write quota is genuinely clever). Was discovering that DROP TABLE doesn't count against the quota a eureka moment or a docs deep-dive?

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#14
Vois 2.0
The ElevenLabs alternative with unlimited generation
100
一句话介绍:Vois 2.0 是一款本地运行的 AI 文本转语音桌面应用,以无限制生成和本地数据保管为核心卖点,解决播客、有声书创作者因按字符计费而不敢反复重录的“预览税”痛点。
Productivity Artificial Intelligence Audio
AI语音合成 文本转语音 本地部署 无限生成 语音克隆 ElevenLabs平替 播客制作 有声书 多角色配音 CLI自动化
用户评论摘要:用户普遍认可本地优先与无限生成的模式,赞赏CLI支持AI代理的自动化潜力,并关注本地生成的音质与速度对比ElevenLabs的表现,以及Expressive引擎是否支持逐句调节音调、情感等参数。另有用户表示UI简洁,乐于接入Claude使用。
AI 锐评

Vois 2.0的聪明之处在于精准切中了专业音频创作者最深层的灰色成本——“预览税”。当云端工具按字符收费时,迭代本身成为一种昂贵的奢侈品,这直接扼杀了创作中最关键的打磨环节。Vois将生成成本降为零,迫使竞争从价格战转向工程能力与用户体验的比拼。其本地化策略不仅是对隐私的承诺,更是对算力成本的结构性规避,但这也带来了硬性门槛:用户必须拥有足够强大的硬件才能换取“无限”的体验。从评论可见,先锋用户已敏锐地将目光投向CLI与AI Agent的结合,这意味着Vois不仅是工具,更是为自动化工作流铺设的基础设施。然而,真正决定其能否替代ElevenLabs的,仍是天秤另一端的语音质感与自然度。目前好评多聚焦于商业模式,而非竞品对比后的最终音质胜出,这暗示产品在“硬核”语音表现上尚未形成碾压性优势。此外,本地生成以消耗用户电力与硬件寿命为代价,所谓“无限”终非免费午餐。Vois的成功路径应在于:以免费迭代换取创作者产出更高质量的素材库,进而通过Pro版的Omni与Voice Design等高级功能实现价值跃迁,而非单纯迷恋“去计量化”的营销叙事。它值得关注,但更需在音质与生态兼容性上拿出决定性证据。

查看原始信息
Vois 2.0
An ElevenLabs alternative on your desktop. Subscriptions get unlimited text to speech: no tokens, no usage meter, no per-character fees. 100+ voices, voice cloning with consent built in, a multi-speaker timeline, mastering, export, and a CLI your AI agents can drive. 23 languages, 600+ with Omni on Pro. Used for audiobooks, podcasts, faceless YouTube videos, game NPC voices, tutorials, and courses, by makers at companies you would recognize. Launch: $10/mo for the life of your subscription.

Hey Product Hunt, Praney here. I build Vois solo from Melbourne.

Since the first Vois launch here, one complaint kept coming back from
podcasters and narrators, and I had it myself: cloud voice tools charge per
character, so every retake of the same paragraph costs money again. I
started calling it the preview tax. You stop iterating, and the read stays
mediocre.

Vois 2.x is my answer: an ElevenLabs alternative that runs on your own
machine. Every subscription has unlimited generation: no tokens, no usage
meter. Retake a paragraph fifty times and your bill does not move.

What is in 2.x:

- Four engines, picked per job: Fast for drafts (about 3x real time on CPU,
about 6x with GPU acceleration on Apple Silicon), Expressive for
delivery, Multilingual for 23 languages, and Omni on Pro with 600+
languages and Voice Design.
- 100+ voices across 21 categories, so a recurring narrator stays
consistent.
- Voice cloning from about 15 seconds of clean audio, with a consent step.
- A multi-speaker timeline with music, mastering, and one-click export.
- Vois CLI for AI agents: Claude, Codex, Cursor, or any agent that can run
a shell command can create projects, generate batches, and export while
you review the plan. Your agent does the talking.
- Since 2.0: encrypted portable backups, reconstructible generation
records, and accessibility across the whole studio.

Scripts, voice samples, and generated audio stay on your machine.

A peek at what I am building next: Quality Guard, which transcribes every
take, compares it against your script, flags misreads, and can regenerate a
bad segment and keep it only if a recheck passes. It is behind a feature
flag today.

For launch week: Subscriber is $10/month and Pro is $14/month(first 100 spots), applied
automatically at vois.so, and you keep this price for the life of your
subscription. Ends August 31, limited spots.

People use Vois for audiobooks, podcasts, faceless YouTube channels, game
NPC voices, tutorials, and course narration.

What would make this fit your workflow? Podcasters, audiobook narrators,
game devs, and anyone wiring voice into an agent pipeline, I am especially
keen to hear from you. I will be here all day.

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@praney_behl nice launch congrats🙌CLI support for AI agents is brilliant, wiring this directly into Cursor or AutoGPT to handle podcast intro scripts completely changes the game. Are there any rate limits or queue delays when executing CLI batches locally?

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@praney_behl How does the local generation compare with ElevenLabs in terms of voice quality and speed

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@praney_behl Congratulations on the launch! Vois 2.0 looks really impressive. The local-first approach and unlimited generation are especially interesting. What feature are you most excited for users to try?
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Best of luck🙌 on Product Hunt today, @praney_behl the vision for privacy-first unmetered desktop AI tools is the exact direction the market needs, can users fine-tune pitch, emotion, or vocal stability on a per-sentence level within the Expressive engine?

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@vikramp7470 Thank you. yes there is fine tuning controls and guides on our blogs

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Congratulations on the release. I just picked a promo code. Thanks, great work. The Ui is simple and I like the ability to connect to Claude for AI automation.

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@penny_berry Thank you, much appreciate it. Please do reach out if you have any feedback.

1
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#15
KiHub
Hardware review platform for KiCad projects
92
一句话介绍:KiHub 是一个为 KiCad 硬件设计项目打造的在线评审平台,让团队无需改变 Git 工作流,即可在浏览器中直观对比原理图与 PCB 版本、进行上下文讨论并自动化检查审批。
Hardware Developer Tools GitHub
硬件评审平台 KiCad PCB设计协作 原理图对比 设计审查 自动化检查 版本管理 Git集成 电子设计自动化 团队协作
用户评论摘要:评论者认可其“不改变Git工作流”的协作理念,认为将PCB评审、讨论与审批集中化是实用改进。目前有效反馈较少,创始人主动征询现有评审流程痛点,但用户尚未提出具体建议或批评。
AI 锐评

KiHub 精准切中了硬件开发流程中“版本管理有了,但评审环节原始”的断层。其价值不在于造新轮子,而在于给已有 Git 上的 KiCad 项目装配了缺失的“视觉化评审层”——这确实是痛点,因为工程师被迫在截图与散落聊天记录中拼凑设计意图。产品逻辑清晰:将 ERC/DRC 等静态检查与人工上下文评论结合,并绑定合并门禁,实质是把软件界的 Code Review 成熟范式移植到硬件域,方向正确且克制的定位(不替代编辑器、不颠覆Git)降低了采用门槛。然而,92票的冷淡反响也暗示了现实困境:硬件团队规模普遍小于软件团队,付费意愿和协作频次存疑;且 KiCad 虽开源流行,其用户多集中于业余或中小型团队,对“审批流”需求未必刚需,而大型企业多用商业 EDA 工具链,难以迁移。此外,可视化 diff 的工程实现难度极高(处理元件移动、网络重命名等),若细微改动识别不准,将迅速消耗信任。其真正的护城河应在于能否成为 KiCad 生态的“协作数据中枢”,而非仅是一个评审工具——若后续能沉淀元件级决策知识库或对接供应链数据,方有更深的想象空间。目前看,是个优雅的“小而美”,但离改变硬件协作范式尚远。

查看原始信息
KiHub
KiHub is a hardware review platform for KiCad projects. Compare schematic and PCB revisions, discuss changes with pinned comments, run automated checks, manage approvals, and keep a traceable review history — without changing your Git workflow.

Hey Product Hunt 👋

I’m building KiHub because there’s still a big gap in the way hardware changes get reviewed.

KiCad projects can live in Git and move through GitHub, but reviewing what actually changed is often surprisingly manual: opening KiCad locally, comparing revisions yourself, passing screenshots around, and discussing design decisions across GitHub comments or Slack.

KiHub adds the missing review layer around that workflow.

With KiHub you can:

  • Compare schematic and PCB revisions visually — see design changes in the browser instead of interpreting raw KiCad file diffs.

  • Start reviews automatically or on demand — from a GitHub pull request or by comparing any two branches, tags, or commits.

  • Discuss changes in context — leave threaded comments pinned directly to a schematic sheet or PCB location.

  • Run hardware-aware checks — including ERC, DRC, schematic-to-PCB parity, BOM completeness, and release readiness.

  • Set review and merge gates — decide which checks are informational and which must pass, and use review status and hardware checks to gate GitHub merges.

  • Review BOM impact — compare component changes, find missing data, and track order readiness.

  • Share reviews outside the workspace — publish read-only links for teammates or external reviewers.

  • Keep every decision traceable — preserve compared revisions, check results, discussions, decisions, and activity in one place.

KiCad stays the editor, and GitHub stays the source of truth. KiHub is the shared workspace where the hardware review happens.

If you’d like to explore it without connecting a repository, we have a gallery of live, read-only reviews generated from public KiCad projects:

👉 Explore the KiHub demo gallery

I’d especially love feedback from people working with KiCad or reviewing PCB designs today: how does your team currently review hardware changes, and what part of that process is the most painful?

Thanks for checking it out!

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Love seeing better tooling for hardware collaboration. Keeping PCB reviews, discussions, and approvals in one place without changing existing Git workflows feels like a practical improvement.

0
回复

@better_shaya Thanks, Shaya! That’s exactly the idea — improve the review workflow without asking teams to replace KiCad or change how they already work with Git. Glad that part came through clearly 🙌

0
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#16
Balsa UI
Create design systems, build with agents
88
一句话介绍:Balsa UI 将设计系统以源码契约形式注入你的代码库,让AI智能体直接基于可扩展的源文件生成UI,解决代理生成代码与设计规范严重脱节、难以同步更新的核心痛点。
Design Tools Open Source Developer Tools GitHub
设计系统 UI组件库 AI智能体 源码分发 组件同步 开发工具 前端基础设施 代码生成 设计技术债 开源生态
用户评论摘要:用户认可“源码而非npm黑盒”契合Agent趋势,但尖锐追问:Agent改写过组件后,上游更新如何调和?开发者确认当前仅做状态分类(未变/本地/上游/分叉),0.8.1将补充文件级diff及强制Agent更新前运行,但自动更新仍保守保留本地改动。
AI 锐评

Balsa UI的本质是给“失控的Agent代码”装上一个监管锚点。它聪明地绕过了传统组件库的封装黑盒,将shadcn的“复制即拥有”模式升级为“契约即同步”——这恰好掐中了AI编程最致命的软肋:大模型生成的UI代码像脱缰野马,而设计系统是唯一可追溯的缰绳。但辩证看,其价值高度依赖“diff/merge”的工程深度。当前方案止步于“告知分叉状态”,虽补上了文件级对比,却仍未定义自动三方合并策略,意味着Agent长期演化后仍会累积社交性技术债。更尖锐的问题是:它默认了“设计系统作为唯一真理源”,但在真实产品中,设计令牌与交互逻辑的迭代常与业务需求耦合,僵硬的注册表可能变成另一种枷锁。短期看,这是AI开发工作流里精准的效率插件;长期看,若不能真正解决“分叉后如何无痛演进”这一终极难题,它只会成为又一件“漂亮的半成品”——不过,在遍地都是“AI一键生成辣鸡UI”的当下,Balsa至少指出了正确的方向:让智能体学会服从,而不是让人类替它们擦屁股。

查看原始信息
Balsa UI
Balsa establishes a clear contract between your design system and a powerful UI library. Its registry delivers the source code your agents can use, extend, and evolve.

this is basically the shadcn model (source code delivered into your repo instead of an npm black box) but pointed at agents instead of humans copy-pasting, which feels like the right instinct given how much agent-written UI code I've seen drift from whatever design system it started from. the question I'd actually want answered before adopting it: once an agent has extended a delivered component and the registry ships an update upstream, what's the story for reconciling the two? shadcn's answer is basically "you're on your own, diff it yourself" - curious if Balsa has anything smarter than that or if it's the same tradeoff.

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回复

@galdayan Hey Gal! Good to know you're using Balsa! That agentic focus really is what I'm trying to achieve with it.

Balsa currently has npx balsa-ui@latest diff <component>. It compares the originally installed source, your local copy, and the current registry version, then reports whether it’s unchanged, local, upstream, or diverged. It currently stops at that classification.

Thanks for raising the gap. 0.8.1 is being published now. The command will also print unified file-level diffs from local source to registry source, and the Balsa agent skill will explicitly instruct agents to run it before updating. Automatic updates will still preserve local and diverged files unless replacement is explicitly forced.

0
回复
#17
AgentR 3.0
Hiring evaluation built for the AI cheating era
84
一句话介绍:AgentR 3.0 是一款由AI代理全权执行的招聘评估工具,通过AI主导的结构化视频面试与内置反作弊验证,解决候选人利用AI作弊导致招聘决策失真、无法识别真实能力的痛点。
Hiring Artificial Intelligence Career
用户评论摘要:评论者认可“AI作弊问题将持续加剧”的前提,认为基于证据而非包装简历的方向正确。但有效反馈较少,有用户仅复述产品宣传语,未提出具体质疑或使用中遇到的问题,缺乏对面试体验、误判率或公平性的实质性讨论。
AI 锐评

AgentR 3.0 精准踩中了后疫情时代远程招聘的信任崩塌点——当ChatGPT能替候选人写简历、做笔试甚至实时提供面试话术时,传统结构化面试的效度确实在归零。其“从验证到评估再到面试”的流水线设计,尤其是将反作弊内置为面试交互逻辑(非事后监控)的思路,是值得肯定的技术方向。但必须泼三盆冷水:第一,所谓“反作弊”本质上是一场军备竞赛,AgentR的逻辑是让回答难以被AI辅助,这只能防御低水平作弊,对于深度人机协同(候选人自己理解答案仅让AI优化表达)基本无效,反而会误伤紧张但真实的候选人。第二,AI作为面试官的政治正确风险极高,结构化自适应提问极易在年龄、性别、口音上产生隐性偏见,且目前没有任何法规允许算法单方面决定录用与否,这在美国若干州已触碰法律红线。第三,从商业看,84票的冷启动数据说明产品仍处于极早期,评论区的附和缺乏深度用户测试反馈,说明其最大的挑战不是技术而是销售——HR部门对新工具的采纳周期极长,除非它能直接证明“证据链”在后续诉讼中可作为法律依据,否则多数企业只会把它当作筛选漏斗,而非最终决策依据。一句话:方向对,但把“防作弊”作为卖点本身,就是在承认AI对招聘的统治力已远超人类——这究竟是解放HR,还是宣告HR的专业判断已被算法判了死刑?值得整个行业深思。

查看原始信息
AgentR 3.0
AgentR is an AI agent that runs the full hiring evaluation, judgment, real work scenarios, and verification, so every shortlist is built on evidence, not a resume and a gut feeling. With Phase 3, AgentR now conducts the entire first interview itself, structured, adaptive, and built to hold up against AI-assisted cheating, so you walk into every decision with the confidence to make the call.
Hi Product Hunt 👋 When we launched AgentR, the problem was noisy resumes. When we shipped v2, the problem was disconnected hiring workflows. Today the problem is different again. Candidates have AI helping them through every stage of an interview, and most hiring tools have no way to tell. So for this launch, we rebuilt the interview itself. AgentR now runs a full AI-conducted first interview, voice and video, structured around how someone actually thinks and works: resume walkthrough, real case scenarios, judgment calls, and hands-on problem solving. It's designed so rehearsed answers and real-time AI help don't hold up, and verification runs before evaluation, not as an afterthought. What's new in Phase 3: ◉ AI-conducted interviews: a structured 25-minute conversation that adapts to what the candidate actually says, not a fixed script ◉ Built-in verification: Our deep research engine checks resumes for consistency before they're evaluated. ◉ Anti-cheat by design: the interview format itself is built to be difficult to fake, not just monitored after the fact ◉ Context-aware CV ranking: candidates are ranked on how their experience actually fits the role, not just keyword overlap ◉ Transparent rejections: candidates get a clear reason when they don't move forward, not silence We built this because we were losing our trust in virtual interviews, and we suspect a lot of hiring teams feel the same way right now. Would love your feedback, especially from anyone running high-volume hiring where this problem shows up first.
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回复

The AI cheating problem in hiring is only going to grow, so building trust back into interviews feels like the right direction. Love the focus on evidence over polished resumes.

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@better_shaya Great and amazing . Today the problem is different again. Candidates have AI helping them through every stage of an interview, and most hiring tools have no way to tell.

0
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@better_shaya Thanks!

0
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#18
Ressearch AI
AI workspace for reproducible scientific research
83
一句话介绍:Ressearch AI 是一个将文献检索、数据分析、可视化与科学写作整合进单一对话式工作区的AI科研平台,通过云端沙箱执行可追溯工作流,解决研究人员在多工具切换中丢失上下文、难以复现结果的核心痛点。
Artificial Intelligence Science Data Science
AI科研助手 科学工作流 可复现研究 文献检索 Python/R分析 数据可视化 学术写作 云端沙箱 生命科学 协作平台
用户评论摘要:创始人说明产品解决科研中工具切换与复现难题,提供免费试用。用户“消费者”非专业人士,试用免疫学(坚果过敏)研究场景后反馈“获取到几篇有趣且有用的论文”,未提具体建议或缺陷。有效反馈暂缺。
AI 锐评

Ressearch AI 的野心是好的——把科研的“脏活累活”装进一个对话式界面,用AI代理在隔离沙箱里跑代码、生成图表、起草论文,并强调“可追溯、可复现”。这确实切中了现代科研的痛点:效率低下、上下文断裂、复现危机。但83票的冷启动和仅一条非专业用户评论,暴露了其尴尬处境:产品宣称的深度功能(如定制Python/R分析、多语言支持)恰恰是专业用户最挑剔、最不愿迁移的环节。一个“消费者”用坚果过敏这种宽泛问题试了一下,得到几篇论文就算“有用”——这离科学家愿意为每月19.9美元付费的距离还很远。

真正的风险在于:Ressearch AI 试图同时做好“文献搜索+代码执行+写作排版”三件事,而这每一件都有极其成熟的垂直工具(如Semantic Scholar、Jupyter Notebook、Overleaf)。它目前的差异化只能是“整合”和“AI辅助”,但整合若不够丝滑,就成了四不像。创始人在评论里问的三个问题很诚实,但也在暗示他们尚未找到真正的“钉子”。或许最该聚焦的是某一类高频、痛感极强的流程(比如“RNA-seq数据分析+报告生成”),而不是服务所有生命科学。复现性是个好口号,科研市场也够大,但让控制欲极强的研究人员交出工作流控制权,需要的不是演示,而是经得起同行评审的案例。目前,它更像一个精致的概念验证,而非杀手级产品。

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Ressearch AI
Ressearch AI brings the entire scientific workflow into one conversational workspace: literature search, data acquisition, Python/R analysis, visualizations, editing, and scientific writing. AI agents execute traceable workflows in isolated cloud sandboxes, making every result reviewable, reproducible, and accessible from anywhere. No setup required.
Hi Product Hunt and everyone, I’m Irwing, founder of Ressearch AI, built by Skyfall Innovations in Peru. We started with a simple observation: researchers often have great questions and valuable data, but lose momentum jumping between papers, search engines, Python/R code, statistical tools, and Word. Colaboration could also be a bit of a challenge. The hardest parts are often turning data into reliable/reproducible analysis, and analysis into clear and traceable scientific writing. Each handoff loses context, adds friction, and makes the final work harder to review and reproduce. We built Ressearch AI to make that workflow continuous. You can begin with a research question, paper, or dataset, and work with specialized scientific agents that can: 🔎 Search and connect literature from 30+ scientific sources 🧪 Plan and run Python or R analyses in isolated cloud sandboxes 📊 Create traceable figures, tables, maps, and 3D scientific objects ✍️ Draft and review scientific writing grounded in project evidence 🔁 Preserve sources, assumptions, code, decisions, and results All exportable to GitHub or local. The goal is not to replace scientific judgment. It is to keep the researcher in control while making every step easier to inspect, reuse, and reproduce. Ressearch AI is built for researchers, graduate students, labs, and scientific teams across the life sciences, from genomics, omics, microbiology, and structural biology to clinical research, drug discovery, medicine, bioimaging, ecology, environmental and geospatial science. It is available in English, Spanish, Portuguese, French, and German, and you can start with a free plan plus our 25 minutes of free taste of the Pro tier. We’d especially value candid feedback on three questions, even if your answer is “none”: 1. What real research task, if any, would you use Ressearch AI for this week? 2. Which tool or manual step would Ressearch AI need to replace before it earned a permanent place in your workflow? 3. At $19.90/month, what outcome would it need to deliver in the first month for you to keep with us? I’ll be here throughout the day. I’d love to hear how you currently move from a research question to evidence, analysis, and a finished manuscript
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@irwing_smith_saldana_ugaz Congrats on the exciting launch Irwing! I am a consumer rather than science expert but a research topic that has been on my mind recently because of my 3yo son is looking into nut allergies and how they develop. I'm curious about immunology to learn more about how his biology works and whether there are ways to help him develop out of these allergies. Trying out Ressearch AI on this use case gave me several interesting and useful papers. Thanks!

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#19
Basedash Public Sharing
Live dashboards for anyone you send the link to
83
一句话介绍:
Data & Analytics
用户评论摘要:
AI 锐评
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Basedash Public Sharing
Basedash Public Sharing turns any dashboard or chart into a tokenized public link. Send it to a client, investor, or stakeholder — they can open a live view without a Basedash account, use its filters, inspect the charts, and sort public tables. Share the whole dashboard or one chart, and let every recipient explore the latest data in their browser. No exports. No screenshots. Just send the link and share the live answer.
Hey everyone, Max here from Basedash. Today we're launching Public Sharing: live dashboards and charts you can send to anyone with a link, no Basedash account required. Choose a dashboard or individual chart, turn on its public link, and send the tokenized URL to a client, investor, or stakeholder. They can open the latest data in their browser, use filters on the shared view, inspect the charts, and sort public tables. We use this ourselves for the dashboards we review with people outside our company. Instead of exporting a new file before every conversation, we send one link and everyone opens the same current numbers. The Product Hunt community gets an extra week on their trial this week. Happy to answer anything.
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The real win here is giving non-technical teams more independence without making data teams answer every small question. Great use case for AI.

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#20
Loopcase
Looping case study videos from your images, no keyframes
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一句话介绍:Loopcase 是一款在浏览器里把静态图片变成无缝循环案例展示视频的工具,专为设计师和作品集创作者解决“不会动效、不想开 After Effects”的临场演示痛点。
Web App Design Tools Marketing
无关键帧视频制作 图片转视频 无缝循环动画 案例研究视频 作品集展示工具 浏览器端视频编辑 模板化动效 4K导出 设计师工具 免订阅免费导出
用户评论摘要:用户普遍认可其解决了“静态案例需要动效”的真实痛点,尤其赞赏免去 After Effects 的复杂性。有评论关注免费导出和浏览器本地处理隐私优势。主要建议尚未明确出现,早期用户更多表达鼓励和期待,未有实质功能批评或缺失反馈。
AI 锐评

Loopcase 的聪明之处在于它没有试图做一个“迷你 AE”,而是精准切入了“作品集案例视频”这个极窄但高频的场景。它的核心卖点“无关键帧、无缝循环”不是炫技,而是对设计师工作流的深刻理解——大多数案例视频只需要一个优雅的镜头运动,而不是花哨的转场堆砌。

从产品策略看,它做了两个极其正确的减法:一是主动限制模板数量,强调“调优而非生成”,这避免了模板泛滥导致的平庸感,也降低了用户选择成本;二是免费计划直接导出真文件,没有水印和试用墙,这既是在建立信任,也是在积累早期口碑——毕竟这类工具的口碑传播远比广告投放有效。

但风险同样明显。首先,它的护城河很浅:核心功能是“图片+预设动效+无缝循环”,一旦被 Figma 或 Canva 这类平台集成,用户迁移成本极低。其次,“浏览器端处理”虽然强调隐私,但也意味着性能上限——4K 导出在本地机器上可能吃力,这会影响专业用户的使用体验。最后,它的目标用户(设计师、机构)虽然付费意愿强,但需求频次低,Lifetime 定价能否支撑长期维护和模板更新是个疑问。

总体而言,Loopcase 是一款“小而美”的工具,它解决的是一个具体且真实的痛点,但天花板明显。如果它能向“案例库管理”或“团队协作展示”延伸,或许能打开更大的空间;若只停留在单一视频生成工具,则很容易沦为“下一个被大厂吞噬的独立小产品”。

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Loopcase
Turn your images into seamlessly looping case study and portfolio videos, right in the browser. Pick a template, tune the motion live, export up to 4K. Every export loops perfectly, no keyframes, no After Effects. Free plan exports real files, no trial wall

Love it Kim and even more when I read how it turn into a real product. Wish you all the best here!

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This solves a very real creator problem. Turning static case studies into something more engaging without opening After Effects is a big win.

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Hey Product Hunt, Kim here, maker of Loopcase. I'm a product designer. Every time I finished a case study, the same thing happened: the work was done, the presentation was tomorrow, and it needed motion. My options were opening After Effects at 9pm or paying a freelancer for something I'd want to tweak five times anyway. So I built the tool I wanted: pick a template, drop in your images, adjust the motion with live sliders, export. No keyframes, no timeline, no render queue. The part I'm most proud of is invisible: every export loops seamlessly, frame zero equals the last frame, guaranteed by how the animations are constructed rather than by trimming. A few things that matter to me about how it works: The free plan exports real files. No trial wall, no locked export button. You can put a Loopcase video on your portfolio today without paying me anything. The template catalogue is deliberately short. Each motion style is tuned rather than generated, because a case study needs one good move, not two hundred mediocre ones. Everything runs in the browser. Your images stay yours. Loopcase has been in open beta with designers and agencies for the past while and their feedback shaped most of what you see. It's early, and that's the point: the first 50 people get founding lifetime pricing, and honest feedback from this community is worth more to me than upvotes. I'll be here all day answering everything. Tell me what's confusing, what's missing, and what would make this useful for your work.
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