Product Hunt 每日热榜 2025-12-23

PH热榜 | 2025-12-23

#1
Super Agents by ClickUp
Tag, message, + manage AI agents across your daily workflows
419
一句话介绍:在ClickUp工作空间内,可像真实同事一样@提及、分配任务和直接沟通的AI智能体,能自主运行端到端工作流,解决团队日常工作中重复、多线程任务的执行与协同痛点。
Productivity Artificial Intelligence
AI智能体 工作流自动化 数字同事 生产力工具 SaaS 团队协作 任务管理 企业级AI 人机协同 智能办公
用户评论摘要:用户普遍认可其“真实队友”的定位和内置集成优势,认为是从“使用工具”到“委托同事”的范式转变。主要问题集中于具体操作边界:如与Google Drive等外部工具的权限集成、对模糊指令的处理机制、记忆回滚能力,以及如何量化AI代理的绩效ROI。
AI 锐评

ClickUp Super Agents的野心,并非在拥挤的“AI生成”赛道上添砖加瓦,而是试图重新定义AI在工作流中的存在形式:从被调用的工具,升维为拥有身份、权限和记忆的“主体”。其真正价值不在于那“500+技能”,而在于将AI深度嵌入既有的数据模型和权限体系,让AI动作与人类操作同轨、可审计、受控。这直击当前企业AI应用的核心痛点——AI与业务系统“两张皮”导致的信任缺失与流程断裂。

然而,华丽的“数字同事”叙事背后,挑战依然尖锐。首先,它本质上是将复杂性封装进一个拟人化接口,但任务拆解、上下文理解与模糊决策的“暗箱”依然存在,用户评论中关于“模糊指令处理”的疑问即是佐证。其次,其能力高度绑定ClickUp生态,在异构的现代企业软件环境中,这种“内嵌优势”可能反而成为跨平台协作的壁垒。最后,当AI作为“用户”在系统中留下大量自动化操作记录时,如何设计不干扰人类、又能清晰追溯的协同界面,是对产品设计的长期考验。

总体而言,这是一次极具前瞻性的架构级革新,其方向代表了企业AI应用的未来:深度融入、行为可控、人机共融。但它能否成功,不取决于AI能否被“@”,而取决于在无数真实、混乱的业务场景中,这些“超级代理”是否真的能像一位靠谱的同事那样,理解意图、减少摩擦、并扛起责任。

查看原始信息
Super Agents by ClickUp
Super Agents are AI teammates you can spin up in seconds to run entire workflows in ClickUp. Anyone can build Super Agents and @mention, assign, direct message, and schedule them to triage, manage, email, code, design, or keep any kind of work moving.

Today we’re launching the first truly human‑like AI agents in the world... ClickUp Super Agents

AI has exploded. Yet 95% of companies are failing at AI adoption. The reality is that AI is not meant to be adopted, instead it should be adapted - to you.

Super Agents are AI coworkers that live inside your workspace as real users. They do real work. You can @mention them, DM them, assign tasks, review outcomes, and trust them to move projects forward - not just generate text.

What makes Super Agents different:

  • They build themselves. Using our state-of-the-art Super Agents Builder, you can vibe your way through powerful and personalized agents

  • They work like real teammates, not tools. You @mention them, assign tasks, DM them, and review outcomes just like a person.

  • They run as actual users with real guardrails. They share the same data model, permissions, and audit trails as humans, so every action is transparent and controlled.

  • They think and act from full context. Fully native to ClickUp, they see tasks, docs, schedules, and conversations together.

  • They learn from human interaction. Every time you give feedback, they listen and improve.

  • They have human‑level memory. Short‑term, long‑term, and editable memory stored directly in docs you can open, inspect, and edit.

  • They keep work moving in the background. They run on triggers and schedules to triage, update, and execute workflows end to end.

  • They have 500+ human skills. These are high quality fine-tuned skills to ensure human-like output and outcomes.

This has been years in the making. We rebuilt our architecture (all custom and proprietary) so humans, software, and AI agents all operate on the same platform and data models.

You lead. Your Super Agents go to work.

This is the biggest step forward we’ve ever taken toward our mission of maximizing human productivity.

ClickUp Super Agents are live today, for everyone. If you try them, I’d love to hear how your team uses them and what you want us to build next.

💜 Zeb
Founder & CEO, ClickUp

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@djcurfew looks like a brand new approach to team work. can I give it access to my Google Drive? and if so, can I manage which folders and files my agent can see?

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@mention  @djcurfew loving the updates. The editable long-term memory stored in docs is super useful. Can teams roll back an agent’s memory if it learns something incorrectly?

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@mention  @djcurfew It's fantastic to see how the product evolves with every new feature you introduce. Great work guys!

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Hey Zeb, congrats on the launch! That 95% of companies failing at AI adoption stat is wild but also… not surprising? Most AI tools feel bolted on, not built in. I’m curious was there a specific moment where you saw that disconnect firsthand?
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Hey PH fam 👋

This launch feels like one of those moments where AI finally starts acting like a real teammate instead of a clever shortcut.

Most AI tools today help you generate things. Then you are left figuring out where that output lives, how it fits, and whether you can trust it to run inside a real team setup.

ClickUp Super Agents take a different path.

Instead of sitting outside your workflow, these agents live inside your workspace as actual participants. You can mention them, assign tasks, review what they do, and trust them to operate with the same permissions and guardrails as everyone else.

That shift is bigger than it sounds.

When AI shares the same context as humans, tasks, docs, schedules, conversations, it stops being a novelty and starts becoming useful. You are not prompting endlessly. You are delegating.

What stood out to me is how balanced this feels.

You are still in the driver seat.
The structure stays yours.

The agents handle the background work that normally slows teams down.

Follow ups get handled. Progress gets tracked. Work keeps moving even when humans are focused elsewhere.

This feels less like automation and more like adding dependable coworkers who never drop the ball on the boring but important stuff.

Curious to see how teams put Super Agents to work and what workflows emerge from this. The ClickUp team is here today, so jump in with questions and first impressions 👇

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@thisiskp_ appreciate you always KP!

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Huge congrats on the launch!!!

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@francescod_ales Many thanks my friend!

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I’d swear I saw a click up launch just last week!
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@jalcantara We're dropping features every week Jorge!!

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@chris_cunningham yeah I just thought ProductHunt forced a 6-month moratorium!
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This is next-level AI teamwork! The idea of Super Agents acting as real coworkers with @mentions, Dms, and task management feels like a game-changer for productivity. Quick question for the makers: How do Super Agents handle ambiguous or incomplete task instructions? Do they ask for clarification like a human teammate would, or is there a way to set default behaviors for those scenarios?

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Neat idea. I bounce between tasks/docs/chat already. Super Agents that can run workflows sounds handy. Curious about guardrails and handoff — can I trust it to email clients from shared inbox? Might try it on our weekly triage.

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Wow, ClickUp is shipping great updates lately. I like the idea of AI coworkers instead of tools. Many congrats on this launch :)
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@rohanrecommends Pumped for you to try it out!

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Congratulations on the launch! This looks amazing!
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@makadiaharsh You're the best Harsh, tysm!

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@makadiaharsh thanks man. Great to see you here!

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Congrats on the launch! This feels less like adding AI and more like rethinking how work actually gets done inside a workspace.

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@abod_rehman it 100% is!

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Have never seen anything like this! And never imagined they would work as perfectly as they do! Truly a huge time-saver!

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@blake_evans1 Insane right? Appreciate you trying it out!

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Wow this is amazing, you guys are on a roll I used ClickUp In the past but this Quite the upgrade. I'm probably not the only one who ran straight to your site get in on this project, I think we've overworked your system LOL after signing it was supposed to a code to my email box but it didn't. And that's no shade on you guys, it's a good thing for you LOL That means people want this.. I'll come back later on and check it out

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@dubd59 Haha I love it Darrell! Appreciate the support and message me chris @ Clickup.com if I can ever help you in any way with ClickUp or any of our new features

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been a clickup user, its the best and seems like its getting upgraded over the time. congrats on the launch ( : 🔥

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@istiakahmad Tysm! We're going to continue to upgrade more and more as well.

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I have got a feature idea: maybe it can show us an agent performance analytics (tasks completed, time saved, accuracy scores, etc.) so teams can measure ROI. :)

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@harsh_jhunjhunuwala Thats a great idea and I believe we could do that if it doesn't already. Feel free to message us that would be fun to setup!

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This is maybe the most ambitious "agents" offering I have seen come to market

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@_jayhack_ Can't wait to tackle it with you!

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I've used Notion, Hubspot and ofcourse Google Sheets as my tracker but man do they all suck. Someone literally gave me a recommendation yersterday to try Clickup. Gonna try it + super agents too!

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@thisissukh_ Perfect timing! Please reach out to me chris@clickup.com if I can help you in any way while you try us out!

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@thisissukh_ no going back :)

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Ok Clickup is crashing it 🔥

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@pasha_tseluyko Can't stop won't stop!

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@pasha_tseluyko or crushing it? Haha widely different
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Congratulations!! Are the guardrails to prevents agents from over communicating?
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Let’s go!
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Congrats! How does onboarding an agent compare to onboarding a human teammate in terms of setup time? :D

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Congrats on the launch, Zeb and team. Excited to try this with a real team workflow :D

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Can't wait to build my ClickUp and Figma Super Agents army! 🔥🔥🔥

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#2
/agent by Firecrawl
Gather structured data wherever it lives on the web
408
一句话介绍:一款能根据自然语言描述,自主搜索、导航并抓取全网复杂、分散数据的API,解决了传统网络爬虫需精确URL且无法处理多步骤、分页等动态场景的核心痛点。
Developer Tools Artificial Intelligence Data
网络数据抓取 智能爬虫 AI代理 数据提取API 自动化工作流 网页爬取 结构化数据 无代码集成 研发工具 SaaS
用户评论摘要:用户普遍认可产品价值,认为其解决了传统爬虫的维护难题。主要关注点集中在:数据存储与处理方式、与n8n/Zapier等工具的集成时间表、如何处理需要登录的网站。同时有用户已将其用于生产环境并给予积极反馈。
AI 锐评

Firecrawl /agent 并非简单的爬虫优化,而是一次对“数据获取”范式的重构。其核心价值在于将“指令-执行”模式升级为“意图-理解-达成”模式。传统爬虫要求开发者精确描述“如何获取”(URL、选择器),而/agent则尝试理解“你想获取什么”,并自主规划路径。这看似是技术便利,实则是将数据获取的认知负担和工程负担从开发者转移给了AI。

产品直击的痛点是真实世界数据的“非结构化存在”与业务所需的“结构化数据”之间的巨大鸿沟。数据散落、需要交互、动态加载是常态而非例外。/agent的野心在于成为数据世界的“通用读取层”,其挑战也同样巨大:复杂网站的稳定性、对抗反爬机制的成本、对模糊意图的准确理解,以及随之而来的伦理与法律边界问题。

从评论看,其早期采用者主要是受够了自己维护爬虫的开发者,他们渴求一个“更省心”的方案。然而,产品要从小众工具走向基础设施,必须回答几个尖锐问题:在动态网页和反爬措施前,其“魔法”的可持续性如何?按量付费的API模式,在大规模数据需求面前是否经济?当用户将关键业务数据流建立在此之上时,其服务等级协议(SLA)和可靠性能否匹配?目前它提供了一个惊艳的“预览”,但要从“有用”变为“不可或缺”,仍需在鲁棒性、合规性与成本控制上证明自己。

查看原始信息
/agent by Firecrawl
Firecrawl /agent is a magic API that searches, navigates, and gathers data from even the most complex websites. Describe what data you want and agent handles the rest. Find information in hard-to-reach places, return single datapoints or entire datasets at scale.
Hey Product Hunt 👋 We're Eric, Caleb, and Nick from Firecrawl. Today we're launching /agent, an API that can gather data wherever it lives on the web. Traditional web extraction requires exact URLs and only scrapes what's on that page. But real data is scattered. It lives across sites, buried in paginated catalogs, hidden in multi-step flows, and you rarely know the exact URLs upfront. We built /agent to handle this autonomously. Just describe what data you need, with or without a URL, and it figures out the rest. It searches, navigates, and gathers information from the widest range of websites, reaching data no other API can. Whether you need one data point or entire datasets at scale, it just works. It's live now in the Firecrawl API and SDKs, and coming soon to n8n, Zapier, and our MCP. You can try it out in our playground: https://www.firecrawl.dev/app/agent Would love to hear what you think. P.S. Launching in research preview, expect improvements as we gather feedback.
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@ericciarla congrats on the launch! when will it be available via n8n?

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@ericciarla I still remember spending days writing and testing web scraping code. The younger generation is lucky they'll never know that struggle! haha. Can't wait to try this out. Congrats!

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@ericciarla big congrats on the launch finally it's now solving the real pain point!

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Really interesting. I would love to use it.
Where is the scraped data stored and how do you chunk it?

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@chilarai It is stored wherever you want it to be stored like in Supabase and you can chunk it yourself

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Congrats team

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@vrijraj Thank you!

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Just tried the playground on a gnarly site — got usable Markdown fast and it saved me time. Excited for the n8n/Zapier hookups you mentioned. Keep shipping! 🔥

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@_ivan1 amazing! n8n is live and zapier is coming soon

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Nice! Any way to pass login data?
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Huge fan!

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@zethleezd Thanks Zeth! Hope you enjoy it

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Exciting update from Firecrawl team!

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`/agent` is so good – congrats on the launch! We're happy paying customers at Dub 😁

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I've been using Firecrawl for several side projects, really amazing tool. Agent is the next logical frontier in their development. Can't wait to try this more extensively.

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Awesome stuff Eric! We've been using the structured data in the single URL scraping data for a while with great results so excited to checking out how much deeper /agent can go and what info we can unlock

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I love this! ❤️ Congrats on the launch. I'm already using it for one of my apps in production and got great feedback so far. Keep it up 🚀

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Outstanding, this is an amazing product. I'm literally in the process right now of setting up that API in my application to pull down leads. I'll let you know how that goes later. Amazing product, good job

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Been hacking together scrapers for docs and pricing pages. Always breaks. This looks like a saner path: give it a URL, get markdown/JSON. Curious how it handles login walls and messy JS tables. If it’s stable, I’ll gladly bin my puppeteer scripts.

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This looks very interesting, well done and keep up the good work!

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Amazing product and team! Great to see how you and the team are executing!

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Wow, what a this thing is off the hook. I love the graphics I love the concept, I love what it does, and yes, I signed up and am getting ready to test this thing out right now

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I really like the autonomous search and navigation idea.
One thing that could be powerful for teams is transparency, will users be able to see or replay how the agent found the data, especially for debugging or trust?

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This is certainly an interesting idea. We have previously built some data mining capabilities using agents as well.

In fact, if you use Claude Code and provide it with sufficient website access, a terminal, a browser, or even its built-in web search tools, it seems capable of retrieving the same unstructured information you want. The only extra step is converting that into structured data. How does your solution differ from this approach?

In my opinion, the most critical factor is how to turn the entire extraction process into a standardized script. This is the true purpose of a web crawler:

1. To take repetitive tasks that would otherwise be costly and labor-intensive.

2. To use script-based automation to lower the cost of repeated crawls.

3. To maintain the ability to update incremental data efficiently.

How are you thinking about this particular aspect?

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Really huge fan of your product. Perfect!

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#3
Aident AI
Build automations with natural language, not workflows
305
一句话介绍:Aident AI是一款智能体驱动的自动化编辑器,用户用自然语言描述需求即可生成可编译为脚本与提示词的“剧本”,在跨工具工作流自动化场景中,解决了非技术用户构建复杂、可维护自动化流程门槛过高且传统工具僵化易断的痛点。
Productivity Artificial Intelligence Marketing automation
智能体自动化 自然语言编程 工作流自动化 无代码开发 AI代理 流程编排 多工具集成 降本增效 企业效率工具 AI原生应用
用户评论摘要:用户肯定其自然语言交互的简易性和“技能+LLM”混合架构的实用性与成本优势。主要问题集中于确定性技能与LLM推理的边界处理、故障应对机制以及实际工作流的边缘情况。建议包括增强编辑器易用性、提供更多模板和集成、并发展本地客户端。
AI 锐评

Aident AI的亮相,与其说是又一个“用自然语言生成自动化”的尝试,不如说它是对当前AI自动化狂潮的一次冷静纠偏。其核心价值不在于“自然语言输入”,而在于其提出的“技能平台”混合架构——将确定性的代码化技能与非确定性的LLM推理明确分离。这直指当前纯提示词驱动自动化方案的阿喀琉斯之踵:成本高昂、运行缓慢且结果不可靠。通过让重复性操作由确定性技能处理,仅在需要高级推理时才调用LLM,它在效率、成本与可靠性之间找到了一个务实的平衡点。

然而,其真正的挑战也潜藏于此。产品试图在“确定性”与“智能”的模糊地带架桥,但用户评论中关于两者“边界”与“故障处理”的疑问,恰恰点明了其技术实现与用户体验的最大风险区。如何确保智能体在复杂、动态的真实业务流中,能精准判断何时切换模式,并优雅地处理失败,这远非一个“编译成剧本”的隐喻所能涵盖。这需要深厚的工程化能力,将AI的灵活性封装进工业级的可靠性之中。

从市场定位看,它避开了与Zapier、n8n等在图形化工作流编排上的正面竞争,转而降低使用心智门槛,瞄准了“想自动化却畏惧流程图的非技术用户”。但这条路同样拥挤。其成败关键在于,能否将其宣称的“智能”转化为用户可感知的、远超传统工具的“省心”——即从“描述它”到“真正搞定它”的最后一公里。团队提到的“从实际使用中学习”和“命令中心”是正确方向,但唯有当平台能持续消化用户反馈,进化出近乎直觉的场景理解与稳健执行能力,才能从“又一个有趣的AI工具”蜕变为不可或缺的自动化基础设施。目前,它展示了一个极具潜力的范式,但距离兑现“让自动化真正自主”的承诺,还有漫长的工程与迭代之路要走。

查看原始信息
Aident AI
Aident AI is an agentic automation editor. Describe what you want in plain English and Aiden turns it into a Playbook that compiles into scripts + prompts. Connect 250+ tools and keep updating the automation through chat as your process changes.

Hi I'm one of the builders! Excited to an early version of Aident AI with you all.

Behind the scene, we built a Skill Platform to smoothly integrate highly reliable code execution with intelligent LLM reasoning. Each Playbook doc is compiled into a mix of skills and prompts, so that the repetitive actions are automatically handled by skills with deterministic logic + integrations, and LLM calls are kicked in only when advanced reasoning is needed. With that, we see huge increase in accuracy & speed, and significant decrease in token cost.

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@yulei_sheng let's go!

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@yulei_sheng How do you decide when to hand off from deterministic skills to LLM reasoning, and how do you prevent edge cases where the boundary causes failures or unexpected behavior in real-world workflows?

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I know many people love N8N, but N8N is not for me.

Aident is fantastic because it's quite straightforward and dead simple to get started, if you are a productivity enthusiast and want to build your own automations even if you don't have any technical knowledge, Aident could be your choice.

Good luck with the launch, Aident team!

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@justin2025 Thanks for the hunting, Justin! love to deliver something that is truly meaningful, and hope it can help some people to make their life easier!

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Hey! I'm Edward, designer @ aident.ai Happy to finally share this on Product Hunt 😊.

As a designer, I care less about “jobs running” and more about whether automation actually helps someone get work off their plate.

What we’re working on next is mostly around that:

  • Making the editor way easier to use, especially when you’re trying to explain real scenarios to Aiden

  • Adding more integrations and skills so it learns from how people actually use it, not just static setups

  • A Command Center that helps you see what’s really happening in your automations, and improve them

  • Native clients so you can build, review, or run things quickly, even locally or on the go

  • And a lot more templates — honestly this is a big one, so our users can start fast and see value early

We’re also planning some brand updates, to better match where the product is going.

Still early days, and a lot of what comes next is shaped directly by how people are actually using it.

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👋 Hey Product Hunt!

I’m Kimi, founder of Aident AI. Super excited to finally share this with you all today.

To be honest, this is a product that I, as a user, have always dreamed of and believed in, even before the ChatGPT moment. I thought this would have been built by existing automation companies, but after a couple years of waiting, I say, FK it! The best way to predict the future is to build it. So, here I am!

This all starts from a frustration I personally experienced when I cold-started my previous startup. I used RPA + Zapier + ChatGPT to automate my outreach pipeline, but it kept breaking and it was really hard to keep it up with my pace of adjusting the outreaching strategy. As an engineer at core, I see something is broken:

AI is smart enough to get a lot done, but we still lack a bridge to communicate and collaborate with them efficiently to get real jobs done. There must be a better way than drag-n-dropping a workflow or coding+deploying your own scripts. The current tools are still pre-AI and especially hard to use for my non-technical friends.

My team and I want to make a difference.

We built Aident as an agentic automation platform, helping users to build automations using Natural Language. Our agent, Aiden, helps you turn your idea into a comprehensive document, called Playbook. You can collaborate with Aiden to make followup changes, either to be more detailed for more precise execution or intentionally more ambiguous to leverage AI intelligence. Also, Aident can integrate with 250+ tools so that you can easily build your workflows across the products you already use.

This is very much a v0 we built along with our early users. We'd really appreciate that you try and tolerate it if breaks. We have a special 50% off Founding User Discount for the first 200 that you can grab today.

Let me know if you like it, hate it, or just sparked some idea - we truly want to hear it all. If you kinda see something special about it, give us an upvote, too!

Thank you so much for checking it out. Happy to answer anything in the comments 🙏

— Kimi

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Hey everyone, I’m Luke, one of the builders here at Aident AI. I’m genuinely excited to finally share this launch with my colleagues and see you try what we’ve been working on for the past months.

The idea for Aident came from a very real pain point. Since the beginning of my degree, I’ve been constantly overwhelmed by the amount of information, tools, and repetitive processes I had to manage every day. Even with so-called “automation” tools, a lot of the work was still manual, fragile, or just mentally exhausting. That frustration is what pushed us to ask: what if automation were truly AI-native from the ground up?

With Aident, I can now build playbooks that closely mirror my real-world workflows, then let Aiden, our agent, execute them for me in a multi-Agent framework consistently and reliably. Instead of babysitting processes, I describe what I want, and the system handles the rest with much higher determinism and quality than what I could manage manually.

A concrete example: I’ve built a playbook that automatically pulls relevant emails and customer data from multiple spreadsheets, then sends hundreds of personalized check-in emails in one run. What used to take hours of context switching now takes a single click by Aident.

This launch is just the beginning, but we’re excited to put Aident in your hands and learn from how you use it. Thanks for being here and for supporting us, please make sure to let us know your feedback, and we will move on from there to shape what we build next.

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I work in marketing, and the role-based scenarios make more sense than generic workflows. Interesting product.
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@jessica_tyy Thanks! That’s great to hear. We’re intentionally designing around real roles, not just abstract or generic use cases.

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I like the idea of skills doing the boring, repeatable stuff and LLMs stepping in only when real reasoning is needed.
Feels much more practical than pure prompt chains. Was that the main motivation behind the platform?

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@abod_rehman hey Abdul, you are absolutely right! wasting tokens and burning GPUs on those super repetitive tasks is a waste of time and money. with that, we already see significant improvements in speed, reliability as well as cost efficiency!

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@abod_rehman Hi Rehman, thanks for asking! Our main motivation is to help people automate repeatable tasks and workflows using AI Agent Teams. We adopted a multi-agent, skills-based approach to help people build a playbook doc in natural language, then use it to automate right away to boost efficiency in the long run.

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Congratulations on the launch 🎉 🎉 !!

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Congrats team! Been messing with Aident for a while. Highly inspiring platform for sure
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@milton_ren Thank you Milton! Please let us know how it went and we hope Aident helps!

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The ‘Describe what you want’ angle is appealing, lets see how it goes. Congrats on the launch though 👏🏻
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👍
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@kpyto Thanks for your support, really appreciated!

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very interesting, congrats team for the launch!

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@youssef_abdelwahed Thanks a lot! Really appreciate the support 🙏

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Cool angle. Describe it, get a Playbook. The compile-to scripts+prompts bit stands out. I've been burned by flaky LLM automations, so deterministic skills sounds sane. Curious about failure handling and auth across tools. Will try on my weekly report flow.

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@alexcloudstar we involve reasoning for failure handling so that when something bad happens, the automation can automatically switch from deterministic approach to intelligent mode for self-recovery. this can make your life much easier! and soon, it can even evolve its own playbook by learning from the issues it encountered!

integration with tools can be pain in the ass. we take care of it by providing first-party integrations with 250+ tools and we handle all the auth management for you to simply oauth to go.

would love to hear your feedback when you get a chance to try your weekly report flow!

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#4
Video to Screenshots
Turn videos into perfect screenshots automatically
219
一句话介绍:一款自动从视频中提取高质量、清晰截图并智能过滤模糊与重复画面的本地化工具,为视频编辑、内容创作者和社交媒体管理者解决了手动逐帧筛选耗时耗力的核心痛点。
Design Tools Productivity Video
视频截图工具 自动帧提取 模糊检测 重复项删除 本地处理 内容创作 视频编辑 效率工具 浏览器应用 免费增值
用户评论摘要:用户肯定其解决长视频(如Zoom录制、婚礼素材)手动“scrubbing”痛点的价值,赞赏本地处理的隐私性。核心建议/疑问包括:能否增加智能场景切换检测(非固定间隔)、明确价格模型。开发者回复确认场景检测在规划中。
AI 锐评

这款产品本质上是一个“视频信息压缩过滤器”,其真正价值不在于“截图”,而在于将非结构化的、线性的视频流,高效转化为可快速扫描、评估和利用的关键帧视觉索引。它切入的是一个看似简单但极其普遍的缝隙市场:介于全功能视频编辑软件(过重)与系统截图快捷键(功能过弱且低效)之间的空白地带。

其宣称的“AI”色彩并不浓重,核心算法更偏向于基础的计算机视觉(模糊检测)和去重。但这恰恰是其精明之处:不过度承诺,解决明确、具体的问题。本地处理是其在隐私敏感时代的核心卖点,也是与云端AI视频分析工具进行差异化竞争的关键壁垒,尤其适合处理客户素材或未公开内容的专业用户。

然而,其商业模式和长期竞争力存在隐忧。首先,固定间隔截取而非基于语义或场景变化的截取,在效率上仍有天花板,这从用户的评论中已见端倪。其次,作为一款功能相对单一的工具,其用户粘性和付费墙的强度存疑。它极易被集成到大型视频编辑软件中作为一个功能模块,也面临来自开源脚本(如FFmpeg组合命令)的潜在替代。它的未来在于能否从“截图工具”深化为“视频内容分析门户”,例如集成初步的对象识别、情绪检测或自动打标,从而将关键帧索引升级为可搜索的视觉数据库,否则可能长期停留在“有用的小工具”层面。

查看原始信息
Video to Screenshots
Extract high-quality screenshots from videos automatically. Blur detection filters out blurry shots. Auto-extract frames at intervals to scan hours of footage in minutes. Smart duplicate removal. Unlimited projects. 100% private - local processing. Free to start.
👋 Hey Product Hunt! I'm Surya, and we're launching v2.0 today. We launched v1 6 months ago and got some really good feedback through DMs and messages. People shared what they needed, so we rebuilt the tool based on those suggestions. Features built for different use cases: For YouTubers & Thumbnail Creators: 🔍 Blur Detection - Automatically analyzes frames for sharpness and filters out blurry transition shots. Only get the sharp, crisp screenshots that work for thumbnails. For Video Editors & Content Creators: ⚡ Auto Extract Frames - Set your interval (every 5s, 30s, 1min, custom) and automatically capture frames throughout your entire video. This is a massive time-saver: • Reviewing client footage - Got 3 hours of wedding footage? Extract frames every 10 seconds and scan the entire thing in under 5 minutes. Identify the best shots, transitions, and moments without watching the whole thing. • Creating contact sheets - Generate visual summaries (like a video index) to share with clients for approval before you start editing. They can see everything at a glance and pick what they want included. • Building storyboards - Extracting frames from reference videos, existing footage, or rough cuts to plan your edit sequence or shot list. Beats scrubbing back and forth manually. • Documenting tutorials/courses - Recording a 2-hour tutorial? Extract frames every 30 seconds to create documentation, study materials, or a quick reference guide without manual screenshots. • Event coverage - Recorded a 4-hour conference or event? Extract frames at intervals to quickly find keynote moments, speaker transitions, or audience reactions for highlight reels. • Finding specific moments - That perfect 5-second clip is somewhere in 90 minutes of B-roll. Extract frames every 5 seconds and find it visually in minutes instead of scrubbing for hours. • Quality checking - Before delivering final videos, extract frames at regular intervals to check for quality issues, compression artifacts, or unwanted elements throughout the entire timeline. For Social Media Managers: 🗑️ Smart Duplicate Removal - Automatically removes exact frames. Saves tons of time when you're processing multiple similar shots or long videos with static scenes. For Power Users: 📸 Unlimited Screenshots - Process as many frames as you need from your videos. 💾 Unlimited Projects - Organize your work across multiple projects. Great if you're managing different clients or campaigns. What stayed the same: Everything processes locally in your browser. Your videos never leave your device. Free to start, no installation needed. Would love to hear your thoughts - especially if you work with video and need screenshots regularly. What else would be helpful? Try it: https://videotoscreenshots.com/ — Surya
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@sooryagangaraj congrats on the launch excited to try it out;

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Looks cool if can improve the quality of screenshots. I usually use Opt + Shift + 3 (or 4 depending on the sequence I wanna screenshot) but it is a fact that I take a photo of a "quality screenshot" intuitively and then have to edit it in Photoshop.

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@busmark_w_nika 
Totally get that workflow - having to edit screenshots afterwards in Photoshop is such a time sink! If you ever work with video content (screencasts, recordings, tutorials), this tool basically does that quality-checking step for you. The blur detection automatically filters frames and only shows you the sharp, crisp shots - so you skip the editing step and just grab the good ones directly.


Would love to know if you try it out! 🙌

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Been scrubbing Zoom recordings to grab stills. Pain. This looks handy. Blur + dupe filter is exactly what I need. Local-only is a plus. Does it pick smart frames around scene changes, or just intervals? I’ll try it on a 2‑hour panel later.

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@alexcloudstar Haha yeah, scrubbing through long Zoom recordings is brutal.

Right now it's interval-based (every 5s, 30s, 60s, or custom) + blur/dupe filtering.

Scene change detection isn't there yet but it's definitely something we're thinking

about - would be super useful for catching slide transitions.

Curious how it handles your 2-hour panel - let me know what interval you end up using!

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@sooryagangaraj Awesome work! Can't wait to try it out. Definitely no more "Print screen"

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@rashiaroraofficial Haha exactly! 😄 Let me know how it works for you - happy to help if you have any questions! 🙌

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Looks great, best wishes for the launch.

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@saeed_salam Thanks a lot 🙌

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oh that's so easy to use!!

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@woojin_song1 Thanks Woojin! Glad it's easy to use - that was the goal! Let me know if you end up trying it out for any projects 🙌

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Love how v2 is clearly shaped by real user feedback. The use-case breakdown makes it very concrete. Curious which feature ended up driving the rebuild the most from v1 to v2?

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@syed_hassan9 Thanks Syed! Honestly, blur detection + auto-extract drove the rebuild. V1 users were manually scrubbing videos and still getting blurry shots. Now it automatically captures frames at intervals AND filters out the blurry ones. Those two features together - automatic capture + quality control - changed the entire workflow. That's what made the rebuild worth it for me.

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Wow! First impression was, who is gonna pay for it but I clearly see it now. Youtubers and content creators will love this. What about the pricing model, is it one shoot or a subscription one?

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@german_merlo1 Thanks for checking it out! 🙌 Let me know if you have any questions

or feedback - happy to help!

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#5
Guideit
Generate Professional Brand Guidelines, In Seconds
201
一句话介绍:一款内置于Adobe Illustrator的品牌指南生成工具,通过上传品牌元素并选择模板,在数秒内自动生成专业品牌指南,解决了品牌设计师在项目后期制作规范文档时耗时耗力、流程繁琐的核心痛点。
Design Tools Branding SaaS
品牌设计工具 Adobe Illustrator插件 设计自动化 品牌指南生成 设计效率 创意生产力 SaaS 设计协作 模板库 设计系统
用户评论摘要:用户普遍认可其解决“创意后”繁琐管理工作的价值,赞赏其内置于Illustrator的流畅体验和Google Drive自动同步功能。核心建议与问题集中在:1. 品牌后续迭代时如何保持指南同步更新而不重新手动工作;2. 强烈要求增加Figma集成;3. 建议开放模板社区,让工具生态持续生长。
AI 锐评

Guideit精准地切入了一个被长期忽视的“脏活累活”市场——品牌视觉识别系统的文档化。其真正价值不在于“生成PDF”,而在于试图将静态的“品牌指南输出”转变为动态的“品牌资产同步与管理”流程。通过深度集成Illustrator和Google Drive,它构建了一个从设计软件到交付客户的微型闭环,其“一键更新”机制直指传统流程中最大的效率黑洞:修改与同步。

然而,其面临的挑战与机遇同样明显。挑战在于其“Illustrator原生”的定位是一把双刃剑。在UI/UX设计主导的数字化时代,Figma已是不可回避的生态位,评论中密集的“Figma何时支持”的呼声即是明证。若固守Illustrator,其市场天花板将清晰可见。此外,其宣称的“自动更新”逻辑能否经得起复杂品牌迭代(如子品牌衍生、多设计师协作)的考验,仍需观察。

其最大的机遇在于,它可能从一个“文档生成器”演变为“品牌单点事实来源”的轻量级入口。如果它能成功桥接Figma、Sketch乃至开发环境,并构建起活跃的模板社区(如用户所建议),它将不再仅仅是一个节省时间的工具,而有望成为连接品牌创造与品牌消费的关键中间层,成为一个轻量级的、以设计为中心的“品牌管理平台”。当前版本是一个出色的利基市场切入,但要想从“有用工具”升维至“必备基础设施”,其生态扩展能力将是下一阶段的试金石。

查看原始信息
Guideit
Guideit is a brand guidelines generator for Adobe Illustrator. Upload your logo, fonts, and colors, choose an Automated Template™ and click Generate. No more dragging logos, typing hex codes, or buying expensive templates. Share one Google Drive link and every update syncs automatically.

Hey Product Hunt 👋

I’m Kwaku, the solo founder behind Akrivi, and today I’m finally sharing something I’ve wanted to build for over 4 years: Guideit — a brand guidelines generator inside Adobe Illustrator.
Excited… and definitely a bit nervous.

I’ve been a brand identity designer for almost 10 years, working with clients across different industries. And there’s one universal truth every designer knows:

👉 Creating brand guidelines is the most boring, draining part of every branding project.
You finish the brand identity, you’re excited… and then the admin begins.

When I surveyed nearly 500 designers, I learned something shocking but unsurprising:
75% of designers spend 8–40 hours creating a single brand guidelines document.
And that’s not just “time wasted” — it’s mentally and creatively exhausting.
Dragging logos. Typing color codes. Fixing spacing. Re-exporting PDFs.
It kills momentum and drains the fun out of the process.

Designers told me they wanted three things:
⚡️Speed — a way to create guidelines fast
🎨 Style — a library of clean, modern templates
🛜 Share-ability — simple online sharing and effortless updates

So I set out to build exactly that.

Guideit:

✔ Generates brand guidelines in seconds
✔ Lives inside Illustrator (no platform switching)
✔ Uses a growing library of Automated Templates™
✔ Lets you share one Google Drive link
✔ Automatically updates with an Apply Changes button
✔ Makes guideline creation simple, fast, and stress-free

After years of wanting to fix this problem… I finally built the tool I always wished existed🪄

How it works:

1️⃣ Upload your logo, fonts, and colors
2️⃣ Choose a template
3️⃣ Click Generate
4️⃣ Share with your client using Google Drive
5️⃣ Apply changes anytime and update online automatically

It’s the fastest way to create brand guidelines. Period.

If you’re a designer or know someone who spends hours building guidelines, I’d truly love for you to try Guideit.

Thanks so much for the support today 🙏🏿 Guideit is officially launching very soon — we’re currently letting people join the waitlist before opening access.

— Akrivi
www.akrivi.io/guideit

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@kwaku_amprako This clearly removes a huge post-branding pain point! How are you thinking about keeping guidelines alive over time, for example, when a client evolves the brand months later or multiple designers touch the same identity, without reintroducing manual work?

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Congrats on the launch — love the Illustrator-native flow and the Automated Templates. The Google Drive auto‑sync is clutch. Curious if a Figma bridge is on the roadmap. 🚀

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This is so well-considered for designers! Building it right into Illustrator so we don’t have to juggle apps — such a smart move ✨

The fun part of branding is the creative stage… but then we always end up drained by tedious work like dragging logos, tweaking spacing, exporting files 😮‍💨

One thought that came to mind: if you ever open it up to let designers submit or sell templates, could this grow into a living "brand guide template community"? 💡
Styles could stay fresh, and the tool itself would really take on a life of its own 🌱

I can already hear so many designers saying “Where have you been all this time?!” 😄
Big congrats on the launch — wishing you huge success 🔥🎉

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Huge congrats, Kwaku! 🎉 Reading your story about wanting to build this for 4 years really hit home. As a fellow solo founder, I know that mix of excitement and nerves on launch day all too well!

You've tackled the classic 'creative vs. admin' problem perfectly. Nobody likes the manual grunt work of typing hex codes. Quick question: Since you started with an Illustrator integration (which makes total sense for print), do you have plans to bridge this into Figma for the web-focused devs later on? Supporting you!

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Yep, this hits a nerve. I’ve wasted silly hours dragging logos and re-exporting PDFs. Living in Illustrator + one Drive link that updates = nice. If the templates aren’t too rigid, this could save me from Sunday night guideline chores. Joining waitlist.

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As someone who’s worked with designers, I’ve seen how draining guidelines creation can be after the fun creative part is done.

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Nice one, congrats team

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#6
Apple Health Wrapped 2025
Your Apple Health Data, Beautifully Visualized.
154
一句话介绍:这款应用将用户苹果健康数据转化为可视化年度报告,在年终回顾场景下,解决了健康数据繁杂、难以直观感知个人年度健康趋势与成就的痛点。
iOS Apple Watch Health & Fitness
健康数据可视化 年度报告 个人健康管理 数据回顾 苹果生态 隐私保护 无广告 生活方式应用 用户激励 社交分享
用户评论摘要:用户反馈积极,认为产品填补了苹果健康数据缺乏“年度总结”的空白,设计直观有趣,无广告体验好。部分用户担忧数据反映不佳年份引发焦虑。开发者回应积极,强调产品初衷是帮助用户为努力感到自豪,而非制造焦虑。
AI 锐评

“Apple Health Wrapped 2025”巧妙地借用了“Wrapped”这一已被Spotify等应用教育成熟的市场概念,将其嫁接到健康数据领域,这是一次精准的定位卡位。其真正的价值并非技术创新,而在于**体验层的数据翻译与情感化包装**。苹果健康应用本身是一个强大的数据仓库,但冰冷而庞杂。“Wrapped”扮演了“策展人”和“故事讲述者”的角色,通过“运动年龄”、“身体歌单”等拟人化、趣味化的洞察,将离散的数据点串联成有叙事感的个人年度健康故事,满足了用户对“意义感”和“社交货币”的双重需求。

然而,其深层挑战与价值一体两面。首先,**健康数据的敏感性远高于音乐品味**。评论中用户对“糟糕年份”的担忧,直接点明了产品可能引发的“健康焦虑”或“比较压力”。开发者虽强调“不为健康游戏化”,但“年度总结”的形式本身带有强烈的评估与比较属性。如何平衡激励与压力,避免让用户陷入数字暴政,是其长期发展的伦理考验。其次,其价值高度依附于苹果健康生态,数据维度的丰富性与准确性受制于平台,未来想象空间存在天花板。

本质上,它是一款优秀的“体验优化型”产品,而非“问题解决型”工具。它不直接提升用户健康水平,而是通过提升数据解读的愉悦感和成就感,间接增强用户对健康管理的关注与持续投入的动力。在健康科技领域从“监测”迈向“干预”的大趋势下,它守住了“回顾与激励”的入口,但若想构建更深壁垒,可能需要思考如何从“年度总结”走向“实时洞察”或“前瞻性指导”。

查看原始信息
Apple Health Wrapped 2025
Health Wrapped turns your Apple Health data into a fun, shareable year-in-review. See how much you moved, worked out, and stayed consistent throughout the year - all wrapped into a simple summary you can actually enjoy. No ads. No spam. Just your health, wrapped.

Hey folks! 👋

Excited to share Apple Health Wrapped with you all.

We wanted to create something that feels less like a dashboard and more like a reflection of your year — the kind that makes you pause, smile, and maybe even share.

Apple Health has a lot of great data, but most of it stays hidden in charts. So we built a simple Wrapped experience that turns your movement, workouts, and habits into stories, moments, and personality insights — like your movement age, your body’s playlist, and the patterns you probably never noticed.

Everything is designed to be thoughtful, private, and easy to share.

Built this with my friend @shivay_madan1 and @aman_jain46.

Would love for you to try it out and tell us what resonated (or didn’t). Feedback welcome 🙏

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Hey Product Hunt 👋


I’m Shivay, one of the makers of Apple Health Wrapped 2025.

This started from a very simple gap - Apple Health has so much data, but there was no Wrapped moment, while Spotify, Strava, Duolingo, Whoop, even sleep apps had one.

So we built Apple Health Wrapped for ourselves first.

We shared an early version with a few Apple Watch users and the response was unexpectedly wholesome.

People started sharing their fitness journeys, streaks, heatmaps, even roasting themselves. That community love is what pushed us to ship this publicly.

The goal isn’t to gamify health, but to help people look back and feel proud of the effort they put in, even on days that didn’t feel like wins.

Built this with my friends @nihal_goyal and @aman_jain46.

Excited for everyone to try :)

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I would rather not try it. :D This one year was awful for me in terms of health. 😭

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@busmark_w_nika you might actually end up being pleasantly surprised xD

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@busmark_w_nika Wishing you a healthy 2026, Nika! <3

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It needed doing; I find the health app so hard to navigate or understand. Good thinking
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This is actually pretty cool! Nicely done folks

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@theishangoswami thanks mate for the ideaa :)

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Have always been an apple watch nerd and thought the gamification of stats there were more than enough for me; till I saw my HealthWrapped 2025. Mind = Blown.

What a solid reflection and now I am super super motivated to crush it even more in 2026.
Let's gggooooo :D

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@navendu_jha hahaha thats so coool!

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Looks like the kind of year-in-review I’d actually look at, not a spreadsheet. My Apple Health is a chaos pile, so a simple wrap would help. The "movement age" bit has me curious. Nice touch with no ads. Gonna run it after my walk tonight.

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#7
Vibe Pocket
Run AI agents like Claude Code, Codex, Opencode on mobile
130
一句话介绍:Vibe Pocket是一个云端平台,让开发者能在手机或网页上便捷运行Claude Code、Aider等AI编码代理,解决了移动场景下开发环境受限、编码效率低下的痛点。
Developer Tools Artificial Intelligence Vibe coding
移动开发 AI编程代理 云端IDE 云端终端 开发工具 多代理平台 GitHub集成 会话持久化 云容器 远程编码
用户评论摘要:用户高度评价其“Vibe Coding”理念,认可AI代理减轻了移动端打字负担。核心关注点在于会话状态的持久性(类似tmux),担心切换应用或断线影响工作流。官方回复确认会话与状态均保存在云端内存,容器在专属VM运行,关闭应用后代理仍持续运行,状态恢复。
AI 锐评

Vibe Pocket的野心不在于做一个简单的移动终端模拟器,而旨在成为“后LLM时代”的云端开发环境中枢。其真正价值并非单纯将终端搬到手机,而是通过封装和集成众多明星AI编码代理(如Claude Code、Aider),将开发的核心动作从“手动敲击”转变为“指令管理与交互”。这精准地戳中了两个趋势:一是开发工具链的“AI原生”化,二是工作场景的彻底流动化。

产品将自身定位为“平台”而非“工具”,通过支持超过15种CLI代理并允许连接GitHub,它试图成为开发者调用不同AI编码能力的统一入口。这种抽象层降低了开发者试验和使用不同代理的切换成本。其云端容器架构保障了会话持久性,回应了移动编码中“随时中断、随时继续”的刚性需求,这是其设计的关键支点。

然而,其面临的挑战同样尖锐。首先,在移动设备上进行严肃开发仍属小众需求,其市场规模有待验证。其次,产品严重依赖第三方AI代理的能力演进,自身壁垒可能不足。最后,如何设计真正符合移动交互逻辑、而非简单移植桌面体验的AI编码工作流,将是其能否突破极客尝鲜圈层、走向更广大开发者的关键。目前看来,它更像一个前瞻性的基础设施拼图,为未来“无处不在的编程”提供了一个颇具想象力的技术原型,但商业化与产品化的道路仍需大量探索。

查看原始信息
Vibe Pocket
Vibe Pocket is a cloud based platform for running AI agents like Claude Code, Codex, opencode, on mobile or web. Connect GitHub, pick an agent, and start building from any device. More than 15 CLI agents are supported including Claude Code, Codex, Gemini CLI, OpenCode, Droid, AMP Cli, Crush, Aider... You can also connect to the terminal and run your apps or any command you want just like on a computer terminal easily. You can also access your running web apps directly within Vibe Pocket.

This is exactly what 'Vibe Coding' should look like! 🏖️

Coding on mobile used to be painful because of the typing, but with agents like Claude Code and Aider doing the heavy lifting, a mobile interface makes total sense now. It feels like the terminal is finally ready for the post-LLM era.

I'm curious about the workflow—does Vibe Pocket maintain the session state (like tmux) if I switch apps or lose connection? That persistence would be key for coding on the go. Congrats on the launch!

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@elevenapril Thank you so much for your comment. ❤️

Sessions are stored in the cloud, with having each container in secure dedicated VM.

And states are also saved in the cloud memory in buffers, even if you close the app or browser tab agent keeps running. When you open the app terminal state is preserved.

Sessions have a timeout depending on the plan you can check out the pricing page. https://vibepocket.com/pricing

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#8
AbleMouse AI edition
Open-source AI cursor control with computer vision
115
一句话介绍:一款通过开源计算机视觉技术,利用鼻子方向控制光标进行免提操作的辅助软件,为行动不便或追求高效多屏交互的用户提供了自然、低疲劳的操控方案。
Open Source Artificial Intelligence GitHub
辅助技术 无障碍工具 开源软件 光标控制 计算机视觉 头部追踪 多平台支持 人体工学交互
用户评论摘要:用户高度认可其开源属性、跨平台兼容性及“用鼻子指向”这一核心交互的自然感和低眼疲劳优势。开发者透露了针对完全失能用户的“无声控制”新方向。整体反馈积极,被视为有价值的辅助与教育工具。
AI 锐评

AbleMouse AI Edition 巧妙地绕开了眼球追踪的技术与体验深水区,选择“鼻尖指向”作为交互锚点,这是一个兼具巧思与务实的产品决策。它本质上不是一项精度至上的尖端科技,而是一个将成熟计算机视觉技术进行场景化、人性化封装的无障碍解决方案。

其真正价值在于“开源”与“模块化”构建的产品哲学。开源确保了技术的透明、可定制和可持续性,这对于需求千差万别的辅助技术领域至关重要。而产品线根据用户身体受限程度进行细分,则表明其从单一工具向系统性能力矩阵演进,意图覆盖更广泛的需求光谱。

然而,其面临的挑战同样清晰。作为一款重度依赖摄像头的软件,其实际体验受环境光线、用户姿态、摄像头素质等因素干扰的鲁棒性有待大规模真实场景验证。与操作系统深度集成、实现如指针加速、微调等精细操作的体验,将是其能否从“可用”迈向“好用”的关键。当前评论集中于理念赞扬,缺乏硬核的障碍场景测试反馈。

总体而言,这是一款在正确方向上迈出坚实一步的产品。它没有沉迷于炫技,而是聚焦于解决一个具体且被主流市场忽视的痛点。其成功与否,将取决于开源社区能否围绕其构建起持续优化的生态,以及产品在复杂现实环境中的实际表现。它提醒我们,技术的温度往往不在于它有多“智能”,而在于它有多“体贴”。

查看原始信息
AbleMouse AI edition
In addition to the DIY edition, AbleMouse has gained a new open-source AI module for face-controlled mouse navigation. Now you just need to point your nose at the desired spot on the screen—regardless of the screen's width—and the cursor will move there. Unlike eye trackers, it feels natural and doesn't strain your eyes. AbleMouse now provides specialized sub-products for various physical needs. View Product Compatibility with User Physical Abilities on the project website.
The solution is fully open-source https://github.com/aradzhabov/Ab... and can be easily adapted to meet the needs of a specific individual. To use AbleMouse AI edition, it is enough that you can turn and tilt your head, and use your eyes and mouth. The mouse pointer is positioned based on the direction of your nose, allowing you to work fast and effectively even with very large screens. MacOS and Windows do not have such a solution built-in. Another very important difference from other solutions is that your eyes remain free, as the tracking is based on the direction of your nose. This provides a much more natural feeling for us as humans and and doesn't strain your eyes. For example, solutions that require you to look at the point where you want to move the cursor demand significantly more effort and feel unnatural. An ordinary person using a hand-operated mouse can look anywhere—AbleMouse allows you to do the same. The code works under both Windows and Mac Os. Unix/Ubuntu support possible — requires testing I also wanted to mention that AbleMouse has become a set of products that work depending on the degree of a person's limitations. You can view the table here: https://github.com/aradzhabov/Ab... Overall, I also see the program as an educational moment. I think many students will be able to pick up something useful for themselves. As we approach Christmas and the New Year, I truly hope that everyone who needs help will be able to receive it. Wishing you a Merry Christmas and a Happy New Year!
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@alexander_radzhabov, I remember commenting on your first launch in September, and here we go again!

I love the direction in which AbleMouse is headed. I will pray it reaches the needy.

Phenomenal usecases, man!!!

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@ashok_nayak , your words and prayers mean more than you know. That's exactly why I am building this — to reach those who need it. Thank you for seeing the heart of the project and for your unwavering support from the very beginning.

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thanks for building such useful tools, congrats for the launch!

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@youssef_abdelwahed Thank you so much—your kind words truly mean a lot!
By the way, your comment on the previous release actually inspired me to explore a new product idea. The current working title is AbleMouse SilentControl. The core concept is voice-based control designed specifically for people who are completely immobile and unable to speak (voice control for those who don’t have a voice). I’m hoping to bring it to life - Q1 2026.

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This is a great solution! Thanks for being so considerate about others!

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@avhijit_nair I really appreciate your kind words—thank you!

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#9
Secret Scan-ta
No more bad Secret Santa gifts
114
一句话介绍:一款利用AI分析收礼人LinkedIn资料,为职场秘密圣诞老人场景提供个性化礼物建议的工具,解决了送礼者因不熟悉同事而选择困难或礼物不合心意的痛点。
Chrome Extensions Artificial Intelligence E-Commerce
AI礼物推荐 秘密圣诞老人 职场社交 个性化送礼 LinkedIn分析 节日工具 社交礼仪 趣味应用 节日季
用户评论摘要:有效评论主要为开发者自述,阐述了产品源于个人真实需求,旨在解决职场中为新同事或不熟悉对象挑选礼物的尴尬。评论未提供其他用户的使用反馈或具体建议。
AI 锐评

Secret Scan-ta 将AI与节日社交仪式结合,其真正价值不在于“礼物推荐算法”本身的技术深度——这很可能是一个基于公开资料分析的轻量级模型——而在于它精准地切入了一个高频、刚需且充满焦虑的微观社交场景:职场秘密圣诞老人。

产品聪明地利用了LinkedIn这一职场人的“标准化公开人格面具”作为数据源,绕开了隐私获取的难题,同时为送礼者提供了一个看似客观、有“数据支撑”的决策借口,从而缓解了“怕送错”的社交压力。它的本质是一款“社交礼仪缓解工具”,其输出的礼物建议更像是一个激发灵感的起点,而非必须执行的命令。

然而,其价值天花板也显而易见。首先,场景极度垂直和季节性,用户生命周期和产品粘性存疑。其次,LinkedIn资料的刻板性与个人真实喜好可能存在巨大偏差,礼物推荐的精准度与惊喜感易受质疑。最后,其商业模式模糊,目前更像是一个展示AI应用场景的趣味实验或引流项目。

总体而言,这是一个巧妙的、场景驱动型AI应用范例,证明了在特定狭窄场景下,轻量级AI也能提供高感知价值。但它更像是一颗应季的“社交糖果”,解决了瞬间的焦虑,却难以成为常年需求的“营养主食”。其成功与否,关键在于能否将短暂的节日流量沉淀下来,或拓展至更广义的、非季节性的社交送礼场景。

查看原始信息
Secret Scan-ta
You think you know what to gift. You don’t. Secret Santa AI does. Don’t ask how.
Hi, I’m Samarth, This started as a small, fun side project that I did not really plan to ship. Christmas was around the corner and I wanted to gift something to everyone at work. Then there was a new joinee. I had not spoken to him much yet, we had no shared jokes or real history. The only thing I had was his LinkedIn profile. I felt this is exactly how some workplace Secret Santa situations feel. So I thought, what if Secret Santa could do better than me here. What if it could look at the same LinkedIn profile and somehow figure out a gift that actually fits the person. I made this mostly for fun, but also because I genuinely wanted to gift something to everyone without it feeling random or forced. You can try it here: https://secret-santa.100x.bot/ If you try it, share what it comes up with on X and tag us @the100xbot. We are curious to see what you are up to, and who knows, we might gift you something as well this Christmas by being your Secret Santa. Cheers, and Merry Christmas 🎄
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回复
#10
Embr
Plan your path to debt freedom
100
一句话介绍:一款通过可视化燃烧动画规划还款路径、追踪进度的应用,在用户进行个人债务管理时,将抽象沉重的债务转化为具象、有激励性的清偿旅程,解决因债务压力大、进展模糊而难以坚持的痛点。
Fintech Payments Data Visualization
个人财务管理 债务清偿工具 进度可视化 隐私安全 动机激励 还款规划 雪球法 金融科技 消费级应用
用户评论摘要:用户普遍认可其通过“燃烧动画”将债务可视化带来的心理激励和隐私保护。核心反馈集中在询问日常使用模式,以及确认是否支持模拟不同还款方案(如增加额外还款)来实时查看对还款周期的影响,开发者确认了该功能。
AI 锐评

Embr的聪明之处在于,它没有将自己定位为又一个功能复杂的预算或记账工具,而是精准切入“债务偿还”这个充满焦虑和挫败感的心理战场。其宣称的“核心价值”——债务燃烧动画与隐私保护——实则一表一里,共同服务于一个目标:重塑用户与债务的关系。

“燃烧动画”是一个极具象征意义的设计。它将抽象的债务数字转化为一个可被“摧毁”的视觉对象,将漫长的还款过程转化为一次次即时的、满足的反馈。这本质上是一种行为设计,通过将“还款”这一财务行为游戏化、仪式化,试图对抗债务带来的无力感,为枯燥的财务自律注入情感动力。这与“雪球法”的心理学逻辑一脉相承,都是通过创造“小胜”来维持动量。

然而,其真正的考验在于“计划”功能的深度。从开发者回复看,它支持基于额外还款的简单模拟对比,这满足了基础需求。但债务偿还的复杂性远不止于此:不同债务的利率差异、突发财务事件、收入波动等因素,都会严重影响最优还款策略。如果模拟场景过于简单,其生成的“自由之路”可能只是一个脆弱的心理安慰,而非经得起推敲的财务计划。

隐私承诺是其另一张牌,在金融数据敏感的时代无疑是加分项。但这同时意味着它放弃了数据聚合分析可能带来的、更具普适性的策略建议,其洞察完全依赖于用户输入。这使其更像一个高度私人的、视觉化的“债务计算器”与“动机维持器”,而非一个拥有金融智能的“债务顾问”。

综上所述,Embr是一款出色的“情绪管理”和“进度追踪”工具,在激发用户主动性、降低心理门槛上可能效果显著。但它能否成为用户通往“债务自由”的可靠路径规划师,取决于其“计划”引擎在财务层面的严谨性与灵活性是否经得起真实复杂生活的考验。它成功地将还债变成了一场更有感的“游戏”,但游戏的最终通关,依然依赖于玩家(用户)自身真实的财务实力与纪律。

查看原始信息
Embr
Visualize your debt payoff journey with satisfying burn animations. Plan payment schedules, track progress, and achieve debt freedom with complete privacy.
The best way to gain freedom from debt is to have a plan and to track your progress along the way.
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@blaineam Great idea, I see a lot potential

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Love how clearly this visualizes progress the burn-down style animations make something stressful like debt feel tangible and motivating. The privacy-first angle is also a big plus, especially for financial data. Interested on how users typically use this day-to-day: quick check-ins vs more detailed planning sessions?

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@syed_hassan9 Because my app does not track users at all I don't have immediate insight on how they typically use Embr, however I know when I used it personally I would use it alongside my budget planning around each pay period and for encouragement to continue focusing on debt freedom. It worked well for me and the planning ability is super helpful to know projections of when different debts can be paid off entirely.

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Congrats Blaine! 🎉 The concept of using 'burning animations' to visualize debt payoff is such a smart psychological hook. Debt can feel so heavy, so adding that tactile, visual satisfaction to the payments is a great way to keep motivation high.

It reminds me of the 'Snowball Method' logic—momentum is everything. Quick question: Does the app allow us to simulate different payoff scenarios (e.g., 'what if I add an extra $50 this month?') to see how it speeds up the burn? Upvoted!

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@elevenapril Agreed, Momentum is very important, thanks for the shout out. To answer your question, yes. The app is designed to encourage you to pay a little extra regularly so you can see the impact that will have on how much sooner you can achieve freedom from debts. It does this by plotting 2 different lines on the chart. one shows just paying minimums and the other shows a strategy similar to the "Snowball Method" factoring in your extra payment you're committing to. Updating the extra payment amount will update the payoff dates and charts in real time so you can quickly and easily tune it until you find what works best for you.

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#11
Filio
Jobsite photo tracking with geo tags and AI notes
98
一句话介绍:Filio是一款AI驱动的施工现场照片记录平台,通过自动附加地理标签、环境数据与AI标注,将杂乱的现场媒体转化为可搜索、可报告的结构化证据,解决了工程建设领域照片管理混乱、数据可信度低的痛点。
Android Photography Artificial Intelligence Construction
施工管理 AI照片分析 地理信息系统 现场文档 项目管理 建筑科技 证据记录 离线应用 视觉资产管理 工程审计
用户评论摘要:用户肯定其从学术研究到产品的扎实背景及流程优化价值。主要反馈集中于两点:一是询问离线工作能力(已获肯定答复),二是出现个别官网访问受阻报告(可能为网络服务问题)。潜在用户认为将照片与图纸结合的功能极具价值。
AI 锐评

Filio的核心理念并非简单的“照片共享”,而是“数据确权”。它瞄准的是工程建设、保险勘察等高度依赖视觉证据的行业里,长期存在的法律与责任漏洞——即海量现场照片因缺乏不可篡改的时空上下文而丧失证明力。其真正价值在于,通过自动化捕获GPS、方位、时间、天气等元数据,并借助AI生成描述,将一张普通的JPG文件“加固”为一份具备审计轨迹的结构化数据资产。

产品由佐治亚理工博士团队打造的背景,既是光环也是战略定位:它刻意与轻量级拍照应用划清界限,强调其学术级的研究方法论与对“数据完整性”的工程化解决。这使其更倾向于一个严肃的B端生产力工具,而非现场协作社交软件。从评论中关于离线功能的关切与官方回应可知,团队深刻理解施工现场网络条件恶劣这一核心约束,技术架构必然围绕“边缘采集、云端处理”进行设计。

然而,其挑战也显而易见。首先,市场教育成本高,需要扭转用户“拍照即记录”的惯性思维,接受一套更严谨但也更繁琐的采集流程。其次,在高度传统、价格敏感的建造业,说服企业为“数据完整性”这一看似隐性的价值付费并非易事。最后,其重度依赖的元数据(如GPS精度)在复杂室内或地下场景可能失效,如何优雅降级保证基础可用性,是实际落地中的关键考验。

总体而言,Filio是一次将学术研究中的“可重复性”与“证据链”思想注入传统行业的尝试。它若能成功,赢得的将不仅是效率提升,更是为整个行业建立数字时代可信视觉证据的新标准。

查看原始信息
Filio
Filio is an AI-powered construction photo documentation platform that turns jobsite media into searchable, report-ready evidence. Field teams capture photos, videos, 360 media, scans, and measured visuals on plan sheets or maps. Filio automatically preserves GPS, date/time, bearing, elevation, and weather, then adds AI captions, AI labels, tags, and custom fields. In the web console, teams control permissions, collaborate with stakeholders, and generate repeatable PDF and Word reports.
Filio’s story did not start with a business plan. It started with a research breakthrough at the Georgia Institute of Technology. As PhD researchers in Computer Science, Civil and Geotechnical Engineering, we (Max Roozbahani, David Frost and Fikret Atalay) spent years analyzing the built environment. We were trained to look for precision and proof. Yet whenever we stepped out of the lab and onto a job site, we saw a massive disconnect. We saw highly skilled engineers, inspectors, and contractors doing critical work, but they were forced to document it with tools that were fundamentally broken. We watched professionals capturing the reality of their projects with nothing more than a standard phone camera. The moment those photos left the site, they lost their value. A photo of a structural issue or a completed milestone is useless if you cannot prove exactly where it was taken or what direction you were facing. We realized the industry did not just have a photo organization problem. It had a data integrity problem. The Problem We Were Trying to Solve We saw teams drowning in "Camera Roll Chaos". Critical project evidence was trapped in text threads, scattered across personal devices, or buried in folders without context. This lack of organization created a liability. In construction, engineering, and insurance, a photo is not just a memory. It is a legal record. It is proof. We asked ourselves why the most important record of the job site was being treated so casually. We wanted to build a solution that respected the complexity of the field. We needed a tool that was as easy to use as snapping a selfie but rigorous enough to stand up in a courtroom or an engineering audit. How Our Approach Evolved We approached building Filio with the same rigor we applied to our doctoral research. We used Evidence-Based Entrepreneurship. We did not simply guess what features might be cool. We treated the problem like a scientific thesis. The Hypothesis: If we could automate the context—capturing GPS, bearing, time, and weather instantly—we could turn a simple photo into an indisputable data asset. The Research: We went to the field. We observed that field crews needed more than just a photo gallery. They needed to see their work on maps and blueprints. The Solution: We evolved Filio from a simple capture tool into a Visual Asset Management Platform. We integrated AI to handle the busy work, like voice-to-text translation and automatic labeling, so teams could focus on building rather than typing. The Filio Difference: Deep Research vs. "Rough Ideas" This is where Filio stands apart from the rest of the market. There are many photo apps available today. Many were built quickly based on a simple idea: that sharing photos should be easier. These tools are often great for showing off a finished job, but they were not designed for data. Filio was created by PhD engineers to solve a harder problem. While others built features for social sharing or marketing, we focused on GIS integration, defensible metadata, and plan sheet accuracy. We built Filio for the teams that cannot afford to be wrong. Filio is the result of high-level academic research applied to the real world. It represents the difference between a rough concept and a solution engineered at one of the top research universities on the planet. We built this platform for the engineers, inspectors, and serious contractors who know that proof is everything.
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Oops! It says https://www.filio.io/ has been blocked

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@chilarai It might be Cloudflare.

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This looks really awesome! I’m a general contractor in the window and door industry and the ability to take document photos and put them on a plan is so valuable. One question I have is, does the app work offline? A lot of job sites don’t have very good internet access so being able to work in an offline mode would be very useful
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@jrbussard Thank you for the comment. Oh yes, that is the major part of Filio that works offline.

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Congrats Max and team! 🚀 Love the backstory here. Taking a project from PhD research at Georgia Tech to a polished, shipping product is a massive journey.

The 'gap' you mentioned between the lab and the actual job site is so real. Most field apps feel clunky, but Filio looks incredibly streamlined.

I’m curious about the tech stack: Construction sites often have terrible connectivity. How does Filio handle the AI processing and sync when the device is offline or in a dead zone? Truly impressive work!

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@elevenapril Thanks, Filio works offline, and the AI part is seamlessly done in the Filio cloud.

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#12
WorkElate
Invisible AI WorkOS. Work Execution without Chaos
70
一句话介绍:WorkElate是一款集成了AI与统一工作流的“隐形”操作系统,旨在通过无缝整合规划、讨论与执行环节,解决团队在多工具切换与工作流断裂中产生的效率低下与混乱问题。
Task Management SaaS Artificial Intelligence
未来工作操作系统 AI工作流 团队协作 任务管理 项目执行 一体化平台 效率工具 无代码/低代码 实时协作 生产力
用户评论摘要:用户肯定其“一体化系统”理念与平静流畅的使用体验,认为其实用性强于炫技。核心反馈聚焦于从现有工具迁移的挑战、复杂工作流的扩展性,以及产品架构如何确保上下文连贯。创始人多次回应,核心挑战在于统一系统状态的架构设计。
AI 锐评

WorkElate的野心并非再造一个Notion或Asana,而是试图成为工作执行的“隐形中枢”。其宣称的“Invisible AI WorkOS”是核心卖点,也是最大赌注。产品介绍中罗列的模块看似大而全,但其真正价值可能在于两点:一是通过“同一系统状态”架构,试图根治“规划-执行”断层这一协作痼疾;二是其“平静、可靠”的产品哲学,在AI功能日益炫目和复杂的当下,选择了一条反直觉的“实用主义AI”路径。

从评论看,早期用户敏锐地捕捉到了关键:它更像一个“系统”而非“工具集合”。这揭示了其深层逻辑——它不满足于充当又一个协同文档或看板,而是旨在成为工作流的底层协议。然而,其风险也在于此。“操作系统”级别的定位意味着极高的集成深度和用户迁移成本。团队能否在保持系统统一性的同时,应对不同行业、不同规模团队产生的极端复杂、非标准化的工作流?其“隐形”的AI如何平衡自动化与用户可控性?评论中关于“上下文”的探讨,正是触及了AI工作流产品的阿喀琉斯之踵:系统理解的“上下文”与人类认知的“上下文”是否总能对齐?

创始人团队“自食其果”的开发模式值得赞赏,这确保了产品核心体验的扎实。但从小团队内部的高频、高共识使用,扩展到外部团队的异构、低频场景,将是其商业化道路上必须跨越的鸿沟。当前版本更像一个精心打磨的“理想型”最小可行系统,其真正的试炼将在面对真实世界混乱、多变的工作需求时才开始。如果成功,它可能重新定义工作流软件的范式;若失败,则可能沦为又一个功能臃肿、试图包办一切的协同套件。其前景取决于能否在“高度集成”与“灵活开放”之间找到那个精妙的平衡点。

查看原始信息
WorkElate
We’re unveiling a powerful chapter in building the Future of WorkOS faster, more stable, smarter, and getting connected. ✅ Bugs fixed ⚡ Latency slashed 🚀 Performance turbocharged Now live in one unified platform: TaskNetic • xNetic • FormNetic Introducing 🎯 BoardNetic: collaborative whiteboarding 📊 DataNetic: AI powered data for real work and insight 💬 Native team chat, built-in One OS. From planning to done.
This year tested us deeply. Building and shaping WorkElate as a bootstrapped startup meant months of learning, refining, and re-architecting and choosing faith over comfort. I’m deeply grateful to the Almighty for the strength to stay the course. 🙏 We focused on fixing the core performance, stability, and flow so work feels calm, connected, and actually gets done, without chaos or tool overload. What’s live today is a strong foundation: faster systems, native team chat, BoardNetic for collaboration, DataNetic for structured work, and unified workflows from planning to execution to done. As we step into year-end reflections and next-year ambitions whether you’re starting a new venture or trying to transform your life and work 100× this suite can be your companion. More is coming in the next few months. We seek your love, blessings, feedback, and early support. 💙
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@ayan_das12 congrats on the launch!

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@ayan_das12 congrats 🎉

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Yo congrats!

I think it’s super bold to change the OS market with AI. What’s the biggest challenge for now while building the product?

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@aira_mongush The biggest challenge was architectural.

Planning, discussion, and execution share the same system state, so actions don’t rely on manual handoffs.

Curious where do you thing context usually matters in this current setup.

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Shipping the mobile app for WorkElate hit differently.

When you know your own team depends on the app every single day, to track work, close loops, and stay aligned “good enough” stops being an option.

We used the mobile app to manage builds, bugs, reviews, and release pressure. That meant if something felt slow, unclear, or fragile, it wasn’t just a user issue it was our issue, immediately.

There were days when fixing one thing broke another. Days when rebuilding the flow felt risky but necessary. And days when the only question that mattered was: would I trust this in a real moment of urgency?

Eating our own dogfood taught me that great products aren’t loud. They’re reliable. They don’t demand attention they quietly support it.

What’s live today is the result of that mindset. And while this is just the foundation, I’m proud of what we’ve built and even more excited about where we’ll take it next.

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@aranya_das1 Congratulations. And happy product launch.

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@aranya_das1  @huisong_li 
Thanks.

What we focused on was eliminating the gap between planning and execution so work doesn’t stall after being discussed.

How do you currently make sure important work actually gets completed?

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Congratulations 👏🏻 🎉 👏🏻 🎉 👏🏻 🎉 👏🏻

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@madalina_barbu 
Thanks.

What we focused on was eliminating the gap between planning and execution so work doesn’t stall after being discussed.

How do you currently make sure important work actually gets completed?

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Congrats team on the launch.🎉🥂
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Building WorkElate while using WorkElate has been one of the hardest and most grounding experiences of my career.

When you truly eat your own dogfood, there’s no hiding.
Every performance lag, broken flow, or tiny friction hits you immediately not as feedback, but as lost momentum in your own workday.

Over the past few months, we rebuilt large parts of our web and AI stack while running planning, discussions, and execution entirely inside the same system. That forced a different mindset: not “does this feature exist?” but “does this actually help work move forward calmly?”

We cut things that looked impressive but added noise. We obsessed over transitions users never consciously notice but always feel. And we kept asking one simple question:
Would I trust this system on my worst workday?

What we’re shipping today isn’t perfect.
But it’s honest. It’s fast. And it’s built around what we personally rely on every day to get real work done.

Proud of the team for choosing depth over shortcuts and excited to keep improving WorkElate with real users in the loop.

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Most AI products today feel like demos wrapped in buzzwords. This felt usable from the first few minutes.

I didn’t need to understand the AI to make progress. It stayed practical..

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Hey folks 👋

Today we shipped WorkElate.

Behind the launch is a simple belief: most teams don’t struggle because they can’t plan, they struggle because work breaks between planning, discussion, and execution.

Over the past months, we kept stripping things down and rebuilding the core so work could move end-to-end without handoffs, copy-pasting, or tool hopping. The focus wasn’t on adding features, but on making the system feel calm, predictable, and dependable when real work is happening.

What’s live today reflects that work: faster performance, native team chat, boards for collaboration, structured data for clarity, and workflows that actually carry work to completion.

Huge credit to the team that stayed patient through iterations and re-architecture especially @shivank_kumar and @aranya_das1 for pushing through details users may never see, but always feel.

This is just the foundation. We’ll keep learning from how people actually use it and keep improving from there.

If you explore it, we’d genuinely love to know what felt smooth and what didn’t. Feedback welcome 🙏

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Finally a OS for Projects. Sounds complete! Looking forward to the features in action! 🔥

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Feels more like a system than a collection of tools.

The OS-level approach to work execution is interesting.

Curious how this evolves as workflows get more complex.

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Tried this briefly and the experience felt surprisingly calm.

Nothing flashy, but things moved forward without much setup.

That’s harder to pull off than it looks.

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Very interesting tool! Good luck Ayan!

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What I like here is the focus on execution, not just planning. A lot of tools help organize work, but fewer help carry it through to completion. Curious how teams transition into this from existing setups.

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Congratulations on the launch 🎉 🎉!!!

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There’s a lot of AI noise right now, and most demos look impressive but feel hollow. This didn’t try to impress me. I just started working. Things moved without me figuring out the tool. Was this intentional, or did I just get lucky with the flow? If it stays this simple as work gets more complex, that would be impressive.

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At time it feels so chaotic to work, with data lying at one place and intent another and without context, never know whether project is making a progress or not. With WorkElate hope to see that getting change. Tried it and its ai based project and work management app is amazing. Will go in deep soon, all the best.
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No matter how many productivity tools we use, the loss of context from one app to the other means more time writing briefs and planning activities than actually doing the work. It’s a nightmare for small teams. I hope WorkElate changes that. Good luck team!

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@harsh_budholiya You’ve described the exact pain we were trying to solve.

Context loss isn’t just inefficient it quietly drains momentum, especially for small teams where every hour matters. Our goal was to make intent, data, and action live in one continuous flow so teams spend less time re-explaining work and more time actually doing it.

Curious: where do you personally feel context breaks the most today: during planning, handoffs, or follow-ups?

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@ayan_das12 Love the focus on work execution without chaos! We built Whisper to help teams communicate better and faster. Your unified WorkOS philosophy aligns perfectly with making work flow better. Excited to see what WorkElate enables! 🚀

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#13
UTMGuard
Find UTM Errors Distorting Your GA4 Data
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一句话介绍:UTMGuard是一款能快速扫描并监控GA4中UTM参数错误的工具,在数字营销和数据分析场景下,解决了因UTM标签错误导致流量数据分类混乱、报告失真的痛点。
Analytics Marketing SEO
UTM监控 GA4数据治理 营销数据分析 数据质量 SEO工具 营销自动化 错误检测 SaaS 数字营销
用户评论摘要:用户反馈主要分为三类:开发者积极寻求早期用户共建产品;部分用户对UTM问题本身认知不足,询问现有工具能否解决;有效评论指出UTM错误具有隐蔽性,且传统方法需依赖BigQuery手动查询,验证了产品需求。
AI 锐评

UTMGuard切入了一个微妙而专业的市场缝隙——GA4数据治理中的UTM参数运维。其宣称的价值并非创造新数据,而是充当“数据质检员”,修复因人为疏忽(如拼写错误、参数缺失)导致的流量分类失真。这暴露了GA4乃至整个营销分析生态的一个固有缺陷:高度灵活的UTM体系如同一把双刃剑,在赋予营销人员巨大定制自由的同时,也因缺乏内置的严格校验机制而成为数据污染的温床。

产品逻辑清晰直击痛点:自动化扫描替代了原本需要导出至BigQuery并通过SQL进行的手动排查,将一项可能需数小时的技术工作压缩至60秒。其真正的商业价值或许不在于“发现错误”,而在于“持续监控”,这相当于为动态变化的营销活动链接提供了实时保险,试图将数据可靠性从一项事后补救的成本,转变为一项可日常运维的资产。

然而,其面临的挑战同样尖锐。首先,市场教育成本高:正如一条评论所示,许多团队对UTM错误的普遍性与严重性并无感知,这意味着产品需先培育市场。其次,工具价值深度存疑:它解决的是“数据录入规范”问题,这本质上是一个可通过内部流程管理与培训优化的环节。对于成熟团队,其是否具备不可替代性?最后,其发展天花板可能较低,功能相对单一,易被大型营销分析平台或更全面的数据质量管理套件以功能模块的形式整合。

总体而言,UTMGuard是一个典型的“锋利小工具”,对依赖精准流量分析的中小团队、营销机构具有即时实用性。但它也警示了SaaS领域的一个常见现象:为解决一个平台(如GA4)的自身设计缺陷或使用门槛,而催生出另一个辅助性工具。其长期成功,取决于能否从“UTM纠错”这个单点,扩展至更广泛的营销数据管道治理,并构建起足够深的用户工作流壁垒。

查看原始信息
UTMGuard
UTMGuard scans your GA4 in under 60 seconds, pinpoints the exact UTMs misclassifying traffic, and monitors them daily.

Hey everyone - Akshay here, maker of UTMGuard.

Really excited to share UTMGuard today.

This started after seeing the same issue again and again across teams and agencies: broken UTMs silently corrupting GA4 data. A missing parameter, a typo, or inconsistent naming sends paid traffic into referral and quietly skews reports. Most teams don’t notice it until much later, if at all.

UTMGuard scans your GA4 in 60 seconds and shows exactly which UTMs are causing problems. It then keeps monitoring daily so new issues don’t slip through as campaigns and links change.

I'm not just looking for users from this launch, I’m looking for a small set of early backers who care about clean GA4 and are open to working closely as the product evolves. In return, I’m offering 40% off for life during the launch using code PHUNT40.

If this is a problem you deal with, I’d love your feedback. Tell me what feels confusing in GA4, what breaks most often, or what you wish tools caught earlier. Your input will directly shape what UTMGuard becomes.


If you'd like to get in touch or have questions about the product, please drop them here or contact me at akshay {at} utmguard {.} com

Thanks for checking it out and supporting the launch 🙏

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I didn't even know this is such a problem. Can't we not segment them in the Analytics tools itself (GA in this case)?

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@onm2022 not unless you export raw data to bigquery and then do manual queries on that data
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Broken UTMs are one of those problems you do not know you have until reports are wrong. UTMGuard catches them early.

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@siddhantmohan1 - true; the flexibility of utm_* also is it’s biggest weakness
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#14
Blobu
Knowledge at the speed of life
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一句话介绍:Blobu是一款AI驱动的知识管理工具,通过即时总结书籍、跨主题连接观点并生成个性化学习指南,帮助用户在信息过载时代,将被动消费转化为主动理解,实现高效知识内化与构建。
Education Artificial Intelligence Books
AI知识管理 书籍摘要 个性化学习指南 知识连接 生产力工具 主动学习 信息过载解决方案 团队协作 快速学习 概念图谱
用户评论摘要:用户反馈积极,认可其作为“个人AI学习助手”的价值,能快速理解主题、简化复杂性。好评集中于体验流畅、信息呈现恰到好处。有效建议较少,评论多为团队庆祝与理念认同,期待未来更多协作与迭代功能。
AI 锐评

Blobu切入的并非蓝海,而是知识管理工具红海中的细分赛道。其宣称的“从摘要到结构化学习指南”的演进,直击了当前笔记工具“收藏即结束”和摘要工具“信息孤岛”的双重痛点。产品真正的野心,在于试图用AI作为粘合剂,构建个人或团队的知识图谱,让知识“复合增长”而非“简单堆积”。

然而,其面临的挑战同样尖锐。首先,从“连接观点”到真正的“理解升华”,AI目前的能力仍停留在模式关联层面,能否触及深层的逻辑与批判性思维整合,存疑。其次,用户体验的“简洁”与功能“深度”之间存在天然张力,如何让用户从被动接收AI总结,转向主动参与知识构建,是产品能否突破工具属性、成为学习伙伴的关键。最后,评论区的“庆功”氛围掩盖了真实的市场检验,45票的关注度表明其仍处于早期探索阶段。

它的价值不在于又一个摘要工具,而在于其框架试图将学习过程“产品化”。如果它能成功将模糊的“知识内化”过程,拆解为可交互、可追踪、可连接的标准化动作,或许能开创一个品类。但当前,它仍需证明自己不仅仅是信息整理的“更优解”,而是学习范式的“颠覆者”。团队对“人类意义构建”的强调是正确的方向,但这条路远比技术实现更为艰难。

查看原始信息
Blobu
Instantly summarize books, connect ideas across topics, and generate personalized knowledge guides — powered by AI.
We built Blobu.ai because learning today is broken—not because information is scarce, but because it’s overwhelming. The future of learning is shifting away from memorization toward rapid discovery. We have more access to books, articles, podcasts, and videos than ever before, yet most of it ends up as scattered notes, half-finished highlights, or content we consume once and never revisit. Knowledge rarely compounds. It just piles up. So the product evolved around a simple question: How do we turn passive consumption into active understanding? That led to a few core ideas: • Go beyond summaries into structured learning guides • Help users connect ideas across books and topics • Let AI do the heavy lifting, while keeping the human sense-making front and center This launch is just the beginning, and we're finally excited to share it with the Product Hunt community. I’d love your feedback—what works, what doesn’t, and where you think this could go next. Thanks for checking it out 🙏
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Big win for the team today!

This launch came from a lot of small steps over time. Late night builds, building on the core ideas, and really figuring out how real people will use Blobu.

Huge credit to the team for the consistency and care it took to get here. Everyone showed up, brought new ideas, and kept moving forward together.

Appreciate everyone taking the time to check it out and support the work. Excited to keep building from here 🚀

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Blobu.ai feels like a personal AI assistant for learning. You can explore any topic in depth and get clear summaries anytime. It feels personalized and helps you understand things faster without making it complicated. A really helpful tool for learning on the go.

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another tool added to my productivity tool list!

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We started Blobu as a side project while building one of our flagship products. What began as a simple experiment quickly proved its value and grew into a product we felt deserved its own launch. Sometimes taking a break to explore new a ideas can help you get to big things.

Blobu is our take on accessible learning, simple to use, fully in your control, and designed to make creating, consuming, and sharing knowledge effortless.

I’m incredibly proud of the team, we pushed this from idea to reality and stayed focused through every iteration. This is only the beginning, and we’re excited about what’s ahead.

If Blobu resonates with you, your support on Product Hunt would mean a lot! Thank you.

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This feels like a meaningful step toward more collaborative AI experiences. Making it easier for teams to brainstorm, refine, and iterate together with AI support is very timely. Wishing the team strong traction on your launch.

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Love the user experience, it shows me just the perfect amount of information before I decide whether I want to read the whole book or not. It’s also great for capturing the main ideas and keeping them fresh in my mind.

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#15
Zedek.ai
Your AI buyer assistant for SaaS decisions
34
一句话介绍:一款AI驱动的SaaS采购助手,通过分析用户现有技术栈和具体约束条件,生成带详细适配说明和风险提示的优先排序候选清单,旨在终结企业软件采购中的信息过载和低效比对过程。
Productivity SaaS Artificial Intelligence
SaaS采购决策 AI助手 软件选型 技术栈分析 供应商短名单 企业采购 效率工具 B2B软件
用户评论摘要:用户普遍赞赏其基于真实约束生成短名单的核心价值,认为其区别于传统目录和通用AI聊天。主要建议包括:支持更多细分软件类别、明确数据实时性、进一步厘清与G2等传统平台的差异。开发者积极回应,强调产品聚焦于“决策层”。
AI 锐评

Zedek.ai的亮相,精准刺中了SaaS采购流程中一个长期被工具忽视的“决策瘫痪”痛点。它并非又一个聚合目录或聊天机器人,其真正价值在于扮演了一个“结构化决策引擎”的角色。

产品聪明地避开了与ChatGPT在泛用性上的竞争,也区别于G2、Capterra等平台的“海量列表+手动筛选”模式。它的核心是输入输出范式的转变:用户输入的是结构化的业务约束(预算、现有栈、合规要求),输出的是一个附带推理过程的决策工件。这直接将工具定位从“信息检索”提升至“分析推荐”,瞄准了采购流程中最耗时、最需要担责的决策环节——这正是采购者愿意付费的关键节点。

从评论看,其“短名单+适配笔记+风险提示”的输出形式获得了早期用户的认可,这验证了市场对“减负决策”而非“更多信息”的需求。然而,其面临的挑战同样尖锐:第一,数据壁垒。其推荐质量极度依赖于庞大、实时且准确的SaaS产品数据库、定价信息及集成兼容性数据,构建和维护这一数据库的成本与壁垒极高。第二,信任构建。作为决策辅助工具,其推荐逻辑的透明度、客观性(如何避免成为付费排名的新马甲)将是用户长期信任的基础。第三,场景纵深。当前模式在标准化、可参数化的软件类别(如CRM、项目管理)中可能表现良好,但在需要复杂业务流程匹配或定制化程度高的领域,其效用可能大打折扣。

总体而言,Zedek.ai展现了一个清晰的、有价值的切入点。但它能否从一款“聪明的过滤器”成长为SaaS采购领域的决策标准,取决于其能否将数据能力、算法信任和场景理解,构筑成真正的竞争护城河,而非止步于一个体验良好的交互前端。

查看原始信息
Zedek.ai
Describe your stack + constraints. zedek.ai returns a ranked SaaS shortlist with fit notes, pricing signals, and risks, ready to share with your team.

Hey Product Hunt 👋 I’m Emmanuel, maker of zedek.ai.

Reality: SaaS buying & Finding is still stuck in 2010.

Most SaaS buying still happens in spreadsheets + tabs.
Not because people love pain - but because there’s no place that turns your real constraints into a decision-ready shortlist.

What zedek.ai is (buyer assistant):
It’s an AI assistant built specifically for SaaS evaluation, not general chat.
You tell it your stack + constraints (budget, region, must-have integrations, security needs), and it returns:

  • a ranked shortlist (not 50 options)

  • fit notes + risks (what will break, what won’t)

  • pricing & integration signals (so you can sanity-check fast)

What makes this different from “just asking ChatGPT”:
zedek.ai is designed to output a decision artifact (shortlist + reasoning), not a conversation that ends with “it depends.”

I’d love feedback on 3 things:

  1. Does the shortlist feel decision-ready?

  2. What’s missing for you to confidently pick #1?

  3. Which SaaS category should we support next?

I’ll be here all day, ask anything.

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@emmanuel_gobiraj 

zedek.ai is interesting because it doesn’t try to chat forever, it helps you decide.

You give it real constraints (budget, stack, region, security), and it gives you a short, ranked shortlist with clear fit notes and risks.

That’s the part most tools avoid.
Less research. More decisions.

Looking forward to seeing how this evolves 👍

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Finally free from 100s of paid software listing sites, fake reviews & pay-to-rank models. I’ve always wanted something like this - something that recommends software based on my existing tech stack, team size and specific use cases, instead of serving the same generic lists every other directory does.

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@anand_nambiar Thank you so much, you nailed the exact problem we’re solving: real recommendations based on your stack, team size, and use-case, not generic lists.

Really appreciate you taking the time to share this...

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The site looks great and easy to navigate. I would suggest you add a few more niche categories so users can drill down further. I love that most of the tools have a demo on them. Hope its intentional :-)

You explained that why this differs from ChatGPT. Any advantage over using something like G2?

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@rumblinglankan Thank you for the comment first, and Great question.

G2 is great for discovery + review volume, but it’s still a directory model, you browse categories, compare pages, and then you do the hard part manually (mapping options to your stack, budget, region, integrations, and risk constraints).

zedek.ai is built for the decision layer step.

Instead of showing “top tools,” it turns your constraints into a ranked shortlist with fit + risk notes and pricing/integration signals so you can decide faster (and explain the decision internally).

And yes, demos are intentional : ) We want evaluation to be “see it → compare it → decide,” not just read reviews.

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It's a big one!
Is it working with a realtime data?

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@jean_cardi Thanks for the comment 🙌 Yes, zedek.ai works with real-time signals where available, and we’re continuously updating the data behind the recommendations.

0
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#16
Startup Studio
Build Real Startups on Full-Stack Infrastructure That Scales
27
一句话介绍:Startup Studio为下一代创业者提供集成了AI开发代理与人类工程支持的AI原生全栈基础设施,在快速构建和扩展真实、可投入生产的应用场景中,解决了开发周期长、成本高及扩展时易崩溃的痛点。
Developer Tools Artificial Intelligence Development
AI原生开发平台 全栈基础设施 平台即基础设施 生产就绪 AI代码代理 快速应用开发 无代码/低代码 初创企业工具 移动端导出 数字资产市场
用户评论摘要:有效评论主要来自产品联合创始人,详尽阐述了产品差异化和定位。其他用户反馈认为其能切实降低早期产品开发摩擦,并认可其雄心。未发现具体问题或功能建议。
AI 锐评

Startup Studio的野心在于试图重新定义“快速开发”的终点——从产出演示原型推向交付生产级应用。其核心叙事“Platform-as-Infrastructure”直指当前低代码/无代码平台及各类开发工具的普遍软肋:演示惊艳,但通往真实、可扩展、集成了复杂商业逻辑(如支付、认证)的产品之路依然布满集成陷阱和重构深坑。

产品将“全栈基础设施”与“AI开发代理”和“人类工程支持”捆绑,构成一个三重价值主张。这看似全面,实则暗含精准的定位博弈:它并非面向纯业务人员,而是瞄准了有技术认知但希望极度压缩工程复杂性和时间的“下一代创始人”。AI代理负责代码生产与重构,人类专家提供架构兜底,这种“AI速度+人类监督”的模式,是当前AI应用从玩具走向工具的关键一步,试图在自动化与可靠性之间找到平衡点。

然而,其真正的挑战与价值验证点也在于此。首先,“生产就绪”是一个沉重承诺,涉及安全、合规、极端场景下的稳定性,这绝非统一技术栈和AI生成代码即可保证,高度依赖其背后“人类专家”的规模与能力,这可能成为其规模化瓶颈。其次,将如此复杂的工程栈抽象化,虽降低了入门门槛,但也可能将用户锁定在其特定范式内,应用深度定制和未来迁移的成本仍需观察。最后,与更成熟的云厂商生态和传统PaaS平台的竞争将不可避免,其差异化优势必须持续体现在“开发速度”与“运维成本”的显著降低上。

总体而言,Startup Studio是一次有洞见的尝试,它瞄准了初创企业从“想法验证”到“真实运营”之间那段依然痛苦、昂贵且专业的灰色地带。如果其承诺的“统一技术骨干”能真正无缝运行,并构建起活跃的组件市场,它有可能成为技术驱动型初创公司的新一代启动引擎。但其成功与否,不取决于概念的新颖,而取决于在复杂真实项目中被碾压时,系统与团队的坚韧程度。

查看原始信息
Startup Studio
Startup Studio is an AI-native full-stack infrastructure built for next-gen founders. It unifies hosting, auth, payments, analytics, security, versioning, and mobile export into one coherent technical system. AI agents write and refactor production-ready code, with human experts supporting architecture and execution. Build and scale real applications fast on reliable, integrated infrastructure.

Hola PH fam! Paula here, co-founder of Startup Studio 👋

As founders, we’ve all felt the same pain:
building a real, scalable product takes too long, costs too much, and breaks the moment you need to grow.

We built Startup Studio to fix exactly that.

Unlike prototype tools that generate pretty demos, Startup Studio is a Platform-as-Infrastructure:
a fully integrated technical backbone + AI development agents + human engineering support that work together to ship production-grade apps, fast.



🔥 What makes Startup Studio different?

🧩 Platform-as-Infrastructure

All core systems are unified from day one:
hosting, auth, payments, analytics, security, versioning, logs, and mobile export, all wired into a single, cohesive platform.

No patchwork. No rewrites. No hidden dependencies.

🤖 AI agents that understand your codebase

Our agents don’t just generate snippets, they write, refactor, and ship production code, handling real architecture, real systems, and multi-step logic.

👥 Humans in the loop

For complex builds, you get a senior engineer supporting architecture and execution, ensuring correctness, stability, and scale.
AI speed + human oversight = confidence.

📱 Web + Native Mobile, out of the box

Your product is automatically compatible with web and mobile.
Push to production in both environments in weeks.

⚡️Production-ready from day 1

Other tools ship prototypes.
Startup Studio ships products that can onboard real users, process payments, scale traffic, and grow without rebuilding from scratch.

🛒 Digital asset marketplace

Use ready-to-ship templates, components, automations, and integrations to speed up complex builds.


💡 What are founders building with Startup Studio?

- Full SaaS products with payments, auth, and analytics
- Vertical micro-SaaS with AI workflows
- Internal tools with real business logic
- Consumer-facing apps that export directly to mobile
- MVPs for early-stage validation that evolve into full products without rewrites

All deployed in hours, not weeks.

👥 Who is Startup Studio for?

Founders who want to launch real, scalable software fast
Indie hackers building products that go beyond prototypes
CTOs & tech leads accelerating teams with AI-powered velocity
Builders who want infra handled so they can focus on product

Drop in the comments: What would you build if your infra, AI, and engineering support were ready on day one? 🚀✨

Happy building!
Paula

3
回复

I appreciate how Startup Studio focuses on equipping creators with actionable support. Helping reduce the friction of early product development and iteration makes this feel genuinely useful. Well done on shipping this tool.

1
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Looks like an ambitious project, wish you success!

0
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#17
Movely
Automated micro-breaks for busy desk workers
25
一句话介绍:Movely是一款能与日历同步的智能健康伴侣,为久坐办公族自动寻找5分钟空隙安排微运动,解决因长时间静止工作导致的健康问题,且无需更换运动服装或手动计时。
Health & Fitness Productivity Remote Work
职场健康 久坐提醒 微休息 智能日历集成 自动化 SaaS 远程办公 生产力工具 数字健康 行为设计
用户评论摘要:开发者亲自介绍产品初衷并获得积极反馈。用户主要询问技术实现(设计生成)、平台扩展(移动端App)、功能细节(可进行多少次运动、是否支持重排)以及未来规划(是否包含器械训练)。整体反馈友好,关注点在于产品可用性与功能延伸。
AI 锐评

Movely切入了一个精准且日益凸显的痛点:知识工作者“静态久坐”与“碎片化日程”之间的矛盾。其核心价值并非提供运动内容,而是充当一个“智能调度系统”,通过日历权限进行间隙挖掘与时机推荐,这本质上是将健康行为植入用户现有的工作流中,而非强行打断它。这种“适配”而非“对抗”的思路,是其相较于简单定时提醒的高级之处。

然而,其天花板也清晰可见。首先,产品高度依赖日历数据的完整性与准确性,对于日程混乱或会议密集的用户,其“自动寻找空隙”的核心功能可能失效。其次,作为初期产品,其运动内容库的个性化和科学性尚未经考验,容易沦为另一个“温和的提醒工具”。用户关于“器械训练”的询问,恰恰暴露了其当前定位的局限性——它更像是“办公室场景的轻量拉伸指南”,与严肃的健康管理尚有距离。

从市场角度看,它巧妙地站在了“企业福利”(关注员工健康)与“个人生产力工具”(减少因久坐导致的效率衰减)的交叉点,具备向B端渗透的潜力。但能否成功,取决于其能否从“一个巧妙的日历插件”演进为“有实证健康数据支撑的个性化健康中枢”。当前版本解决了“时机”问题,但更关键的“动力”问题(用户为何要坚持)和“效果”问题(是否真正改善健康),仍需深度构建。它的真正挑战在于,如何让用户在5分钟里获得的即时收益(清醒、放松)足够明显,以形成稳固的习惯闭环。

查看原始信息
Movely
Movely is the first calendar-aware wellness companion that fixes your posture without breaking your focus. It syncs with your Calendar to automatically find 5-minute gaps for micro-movements. No gym clothes, no sweat, and no manual timers.
Hey PH 🤙 Long time no see! Oli here, I'm a software engineer who spent way too many hours without moving in my workdays. I realized that my biggest health problem wasn't a lack of gym time but the 8 hours of total stillness between 9 and 5. I tried setting phone alarms, but they always went off in the middle of deep work or meetings. I just ended up snoozing them. I built Movely to be the 'smart' reminder I actually needed. It looks at your calendar, finds the gaps, and suggests 5-minute movements you can do in your regular clothes. Would love to get your feedbacks to make you love this product and add what's missing! Cheers and happy moving 💛
7
回复

@olivier_dumas Hey!
Love the design, did you generate this vibecoding?
Will you release a mobile app aswell?
Cheers!

1
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@olivier_dumas How many sessions can I do ?

1
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Love the idea Olivier! I’m a big fan of tech products that encourage a less sedentary lifestyle. Any plans to add exercises using gym equipment?
1
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@gabriel_amzallag Thanks Gabriel!
I do have plans for exercises with gym equipment but at home, it will be available in a later version of the product!
Cheers

0
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Amazing! Can I reschedule a session if I miss it?

1
回复

@paulcharbogne Hey Paul!
Thanks for the comment, actually you can find all the sessions in your dashboard, reschedule it if needed on the calendar UI :)

0
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#18
PlugFast
Build Professional Chrome extensions in minutes, not weeks
23
一句话介绍:PlugFast是一款提供生产就绪型模板的工具,帮助开发者在几分钟内快速构建专业级Chorme扩展,解决了从零搭建时重复编码、配置复杂且易出错的痛点。
Chrome Extensions SaaS Tech
Chrome扩展开发 开发者工具 项目模板 生产力工具 SaaS辅助 快速原型 代码脚手架 Manifest V3
用户评论摘要:评论主要为创始团队自我介绍与产品理念阐述,强调其源于自身开发痛点,旨在简化流程、避免重复工作。团队积极寻求反馈,但暂无外部用户提出具体问题或建议。
AI 锐评

PlugFast瞄准了一个看似微小却真实存在的缝隙市场:Chrome扩展开发的“脚手架”阶段。其价值不在于技术颠覆,而在于对开发者工作流中“脏活累活”的标准化封装。产品标语“几分钟,而非几周”直击要害——将开发者从重复的manifest配置、权限申请、后台通信、认证流程等基础但易错的环节中解放出来。

然而,其面临的挑战同样清晰。首先,目标市场容量存疑:专业开发者群体是否足够庞大,且普遍愿意为一份“最佳实践”模板付费?其次,模板产品的护城河极浅,极易被复制或开源替代品冲击。评论区内仅有团队自述而无真实用户反馈,这使其宣称的“实用性”尚未经过市场验证。

真正的考验在于,它能否从“一份好模板”进化为一个“生态入口”。如果仅停留在一次性销售代码,其商业天花板将非常有限。未来的想象空间或许在于:围绕扩展开发,构建插件市场、部署服务或集成平台,形成闭环。目前看来,产品理念值得肯定,但团队需要更快地收集真实用户数据,迭代模板,并证明其模板在复杂生产环境下的稳定性和扩展性优势,否则很可能只是一个叫好不叫座的“精致小工具”。

查看原始信息
PlugFast
Save hours building a Chrome extension for your next SaaS. Start with a production-ready template, avoid setup errors, and ship faster 🚀
Hello everyone! 👋 We’re DevDuo V.O.F. — Ahmed (22) and Eray (22) from the Netherlands 🇳🇱 We founded PlugFast to enter the Chrome Extensions market and contribute something practical: a simple, affordable, high-end boilerplate that helps makers build and ship Chrome extensions faster 🚀 Our goal is to remove complexity, setup errors, and wasted time, so founders and developers can focus on what actually matters: their product. 🎉 Special offer: get €50 / $58 off your first template — the discount code is in the link when you purchase via our site! We’d love to hear your thoughts, feedback, or questions — and who knows, maybe we can build something great together 🤝 Thanks for checking out PlugFast! 🙌
8
回复

Hey everyone! 💛

This is our very first time launching on Product Hunt, so we’re still learning and figuring things out as we go.


We’d love to hear your honest feedback; what you like, what you’d improve, or what you’d want to see next. Every comment really helps us grow and build PlugFast into something genuinely useful.


Thanks so much for checking us out and for being part of the journey 🚀

The PlugFast team

5
回复

If you’re curious what’s inside the template... 👀, it’s also fully shown on the site.

We’ve added a clear breakdown of the structure, tech stack, and included features so you can quickly see what you’re getting.

As this is our first Product Hunt launch, we’d genuinely love any feedback or thoughts! 💛

5
回复

Hey Product Hunt, Ahmed here — one of the makers of PlugFast! 👋

The idea for PlugFast came from a pretty simple frustration: we kept building Chrome extensions for projects and clients, and every single time we were rewriting the same foundation from scratch — auth, backend setup, structure, deployment, you name it.

We started wondering: why isn’t there a clean, production-ready starting point that actually saves time instead of adding complexity? That question slowly turned into PlugFast.

This is our first time launching on Product Hunt, so we’re learning a lot along the way. We’d genuinely love to hear your thoughts — what’s useful, what’s missing, or what you’d want to see next. Thanks for checking it out 💛

4
回复

Hey everyone — Eray here 👋

From the building side, one of the biggest challenges was finding the right balance between flexibility and simplicity. We didn’t want a “bloated” template, but we also didn’t want something that only works in perfect demo scenarios.

We went through multiple iterations to make sure the structure is realistic, scalable, and actually usable in production — especially with things like Manifest V3 limitations, backend communication, and auth flows.

This is our first Product Hunt launch and honestly a big learning experience for us. If you have questions, feedback, or ideas — we’re more than happy to discuss them here 🙏

3
回复
#19
GLM-4.7
Advanced coding & reasoning with multi-turn thinking
21
一句话介绍:GLM-4.7是一款专为编程与推理优化的先进开源模型,通过“Preserved Thinking”功能在多轮复杂任务中保持推理上下文,解决了开发者在进行深度编码时思维链易中断、上下文丢失的核心痛点。
Open Source Artificial Intelligence Vibe coding
开源大语言模型 代码生成 逻辑推理 多轮思考保持 开发者工具 AI编程助手 SOTA模型 智能体兼容 编程优化 上下文管理
用户评论摘要:评论者(疑似项目相关方)积极评价版本快速迭代及前端改进,重点称赞“Preserved Thinking”功能对维持复杂编码任务上下文的价值,并推荐其与主流编程智能体的兼容性及GLM Coding Plan的性价比。目前评论样本单一,缺乏广泛用户反馈。
AI 锐评

GLM-4.7的发布,与其说是一次技术飞跃,不如说是对当前开源AI竞技场核心赛道的精准卡位。其主打“Preserved Thinking”功能,直击大模型在复杂、长周期代理任务中的阿喀琉斯之踵——状态与思维链的丢失。这并非全新概念,可视为对CoT(思维链)和智能体记忆机制在工程化层面的深度打磨,旨在将学术界的“推理”更可靠地转化为产业界的“生产力”。

然而,其真正价值可能不在于单一功能的炫技,而在于其作为“开放权重”模型所构建的生态策略。强调与Cline、Claude Code等流行编码智能体的兼容,实质是降低集成门槛,试图以模型层身份快速嵌入现有开发者工作流,而非重建生态。这种“赋能现有工具,而非取代”的定位是务实的,但其长期竞争力将取决于:在同等参数规模下,其推理精度、上下文保持的稳定性以及对计算资源的实际消耗,能否对闭源竞品形成足够性价比优势,或在特定垂直场景(如复杂系统调试、学术代码生成)建立护城河。

当前21票的冷清热度与单一、疑似官方的评论,也折射出其面临的核心挑战:在Llama、DeepSeek等开源巨头的声量挤压下,如何突破小众圈层,让广大开发者真正感知并验证其“Preserved Thinking”在真实项目中的效能提升。若其宣称的“状态保持”能经得起GitHub上各种刁钻issue和PR的考验,它或许能成为专业开发者工具箱中一把犀利的特种手术刀;若仅停留在宣传层面,则可能只是又一颗划过拥挤赛道、迅速黯淡的流星。

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GLM-4.7
GLM-4.7 is a SOTA open-weight model optimized for coding and reasoning. It features "Preserved Thinking" to maintain reasoning context across multi-turn agentic tasks. Compatible with tools like Cline and Claude Code.

Hi everyone!

Z.ai has been shipping like crazy recently. They just updated their flagship model from 4.6 to 4.7, and the frontend capabilities and aesthetics have improved drastically.

The most interesting part to me is the "Preserved Thinking" feature. It basically allows the model to remember its reasoning steps across multiple turns, which is huge for complex coding tasks where context usually gets lost.

As always, it works seamlessly with your favorite coding agents like @Claude Code , @Kilo Code, @Cline etc.

Also, the GLM Coding Plan is great value for money. It is already quite popular among developers, highly recommend checking it out.

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@zaczuo Congrats on the Launch.

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#20
The AI Library
World's First Gamified AI Launchpad
19
一句话介绍:这是一个通过游戏化榜单和真实用例筛选,帮助创业者、创作者和团队高效发现实用AI工具的平台,解决了信息过载和选择困难的核心痛点。
Productivity Artificial Intelligence Tech
AI工具发现平台 产品推荐 游戏化榜单 提示词库 社区驱动 效率工具 信息筛选 真实用例 产品评测 创作者经济
用户评论摘要:产品发布者阐述了解决AI工具市场信息混乱的初衷,强调以真实用例和社区信号为核心。评论者普遍认可其价值,认为能帮助很多人,但暂无具体功能反馈或批评建议。
AI 锐评

The AI Library 切入了一个看似拥挤但实则低效的赛道——AI工具导航。其宣称的“游戏化启动台”和“真实世界用例”是试图在“AI工具黄页”红海中建立差异化的关键点。

产品真正的赌注在于其筛选机制。它试图用“实时排行榜”和“社区驱动发现”来对抗营销噪音,这本质上是将“Product Hunt”的投票模式垂直应用于AI工具领域。然而,这恰恰是其最大挑战:一个新兴平台的初始社区能否产生足够高质量、无偏见的“真实信号”?早期用户群体(尤其是创始人、创作者)的偏好,很可能导致榜单偏向营销、设计或内容创作类工具,形成另一种视角的“信息茧房”。

其“扩展中的提示词库”是更务实的附加价值,它试图绑定工具与应用场景,但提示词的质量管理和版权问题将是隐忧。目前19票的冷启动数据也表明,它尚未引爆市场关注。

总体而言,其价值不在于“又一个列表”,而在于能否成功构建一个可信的、基于真实使用反馈的过滤层。如果它能严格践行“基于用例而非热词”的承诺,并吸引足够多元和专业的用户贡献数据,它有可能从“展示橱窗”进化成“质量认证”平台。否则,它极易沦为另一个依赖编辑推荐或隐性广告的导流网站,在信息过载的浪潮中增添一片浪花。

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The AI Library
The AI Library is a simple way to discover useful AI tools without stress. We curate and review AI products based on real-world use cases. Discover new launches, explore top tools through live leaderboards, utilize our expanding prompt library, and see what people are actually using and recommending. Built for founders, creators, and teams who want clarity, trust, and AI that works in the real world.
Hey friends 👋 Maker here. If you’ve tried finding good AI tools lately, you know how messy it’s become. Endless lists, hype posts, and tools that all sound the same. It’s hard to tell what actually works and what’s just noise. We built The AI Library to fix that. The idea was simple: create one clear place where people can discover AI tools based on real use cases, not buzzwords. Tools you can actually use for work, building, creating, or shipping products. As we built, our approach evolved. We leaned more into real signals and less into marketing claims. That’s why we added things like live leaderboards, a growing prompt library, clearer product categories, and community-driven discovery so the best tools naturally rise to the top. We’re excited to launch today and have the Product Hunt community be the first to explore it, break it, and tell us what’s missing. If you’re building with AI or trying to use it better, we hope The AI Library saves you time and helps you find tools that actually deliver. All feedback is welcome 🙏
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this will help lots of people

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