PH热榜 | 2026-08-25

Hey Product Hunt,

Sid here, co-founder at akta.pro. Private company data and signals API for agents, priced by consumption.

We were building AI agents for private markets and kept hitting the same two dead ends.

• Legacy databases have company data, but they gate it behind a UI, charge by seat, carry no signal layer.

• Search APIs return what ranks on SEO. Your agent burns tokens reading 100s of pages to find one event.

akta.pro gives an agent both sides, already structured.

Company data: 20M+ companies with 70+ fields, i.e., 2x coverage of PitchBook, 4x depth of ZoomInfo/Apollo.

• Fundamentals: firmographics, management, funding history, investors, revenue and financial estimates.

• The fields most databases skip: competitive moat, gtm motion, business model, tech stack, AI maturity.

News and signals: monitor a company, a sector, or a topic in plain language.

• Feeds are de-duplicated, matched to the right company, and scored for impact and sentiment.

• Tagged across 100+ event types like funding round, exec change, expansion etc., that work as triggers.

• Alternative signals tied to the same company ID: headcount trends, web traffic, jobs, social posts, reviews.

On cost, company data runs 5x cheaper than legacy databases like PitchBook. News runs 10x cheaper than putting the same work through Claude or Parallel search APIs, where retrieval comes out of your token spend.

Used today by AI builders shipping agents, GTM teams triggering outbound, and investors screening startups.
Works as an API, over MCP, or CLI.

Try for free. Code PH50 gets you 50 credits: playground.akta.pro/signup/?coupon_code=PH50

If you have evaluated legacy databases, news or search API providers, or GTM intent data, I am happy to do a specific comparison in the comments.

Here all day, and the critical feedback is the useful kind.

Happy to go deep on the technical side.

Reasoning models changed the economics of proprietary data. For years the winning move was a large team of analysts manually cleaning, normalizing and QAing structured datasets. That model is going obsolete.

Demand growth is in agents now, and agents do not want a handful of structured fields in a subscription model. They want a large, reliable corpus of structured qualitative knowledge they can reason over and scale consumption as needed. That changes how you architect the platform.

So we made entity resolution the foundation everything else sits on. Every company gets a canonical identity connecting parents, subsidiaries, products, executives, investors, news and hiring signals.

Once identity is solved, coverage stops being a fixed list you either have or lack and becomes an extensible graph, where anything new resolves against identities that already exist, including data you bring in yourself.

The real-time news pipeline runs on those same identities, with no batch refresh window. Every article goes through:

• Deduplication and entity resolution back to company IDs

• Classification against an 100+ event taxonomy

• Mapping to NAICS, SIC, IAB and IPTC codes

• Scoring for impact, sentiment and story centrality

Each of 20M+ companies are tagged to 30k+ industry codes and qualitative source-traceable data across 70+ fields.

The noise gets filtered along the way, and whatever survives is queryable the moment it lands.

The schema is built for reasoning over a corpus rather than browsing rows in a dashboard, which changes the interface too. Everything is API-first, with MCP and CLI as first-class surfaces built for token efficiency and composability inside agent workflows.

The goal is simple: make private markets data programmable for anyone building with AI.

Try for free. Code PH50 gets you 50 credits, no card required: playground.akta.pro/signup/?coupon_code=PH50 — If anything in the docs at https://docs.akta.pro/ is wrong or hard to follow, tell me and it usually gets fixed the same day

I like that this goes beyond basic company profiles. Signals around funding, hiring, and other events can add much more context.

Would love to see webhooks for specific company events eventually. That could make the outbound automation possibilities huge. What do you think?

The 100+ event signals are what caught my attention. Having those alongside company data could make research much faster.

The combination of private company data and real time signals is probably more useful than either one along.

Having more coverage is great, but the real test is whether the data stays actionable for teams using it daily.

How often are company profiles updated? Private company data can change pretty quickly.

I’ve worked with company research tools before, and keeping data organized is usually the hardest part.

Interesting Concept. Congratulations on the Launch. @saswat_nanda2 @siddhant_masson @bharat_garg6

Congrats on shipping! Reliable private company data through a clean API is essential for autonomous AI agents to make real decisions. Simple, high-utility infrastructure for dev teams.

congrats on the launch!

Love that you built this API-first for AI agents rather than dashboards, giving agents structured company signals to act on feels like the real unlock here.

Congratulations on the launch! Private-market data definitely needed something more developer-friendly for a while. Akta seems like a great solution.

I question how teams measure success after using this API. would the main benefit be saving research time or finding better business opportunities?

I enjoy seeing tools that improve private market research. I would ask how akta.pro manages global coverage since company information varies widely across regions and markets.

More data can also create more noise. How do you help users focus on the signals that actually matter?

Can users define their own triggers or signals based on the type of companies they’re tracking?

This is great. Congrats, Siddhant and team.

Since those are synthesized rather than reported data, would I be able to see what a given moat call was drawn from, or do I take the field as given?

Cool. Can you set up notifications when a specific signal is triggered? And can you create custom signals?

How granular are the sentiment and impact scores? Can developers access the underlying scoring fields through the API??

How do you handle companies with very limited public information?

As a developer, having this available through API, MCP, and CLI makes the product flexible and interesting to use. Congrats on the launch!

How do you keep the event signals fresh, especially when a company has very little public information?

Per seat pricing on company data always punished the wrong person, since I need enrichment in bursts around a campaign and then not at all for weeks. On the signals layer, how fast does something like a funding round or a hiring spike actually show up after it happens?

20M+ companies with 70+ fields is a serious amount of coverage. Congrats to the team! 🚀

Hello Product Hunt 👋🏼

As someone who spends a lot of time building with AI, few things are more frustrating than hitting Claude’s usage limit right in the middle of focused work.

You rarely know how much of your session is left, when it will reset, or whether one long conversation is quietly burning through your tokens.

@surbhi_singla2 is a Claude and Diet Coke maxi who turned this painfully familiar problem into a fun little product.

I’ll let her tell you more about it.

Over to you 👇

love that i can get the last juice from my claudee

Monitoring tokens got really interesting with the fizz of a soda Can opening ASMR sound. Super awesome to use it.

I'm on Max plan but I have 50+ friends who're on $20 plan and they all will love this. Forwarding them this - rad video. Super cool stuff Surbhi 🔥

love it, my friend made a diet coke can opening couple of months ago, u just click and hear psssst sounds that is it but this one is a good use of making it club with claude's limit.

Tracking rate limits real-time so workflow doesn't hit a wall mid-prompt is super useful. Nice launch!

Sorry guys, just wondering, should I install something before use?

Hahah loved the video! You deserve being at top here! Wish you all the best guys!

Useful and love the retro pixel design on the Diet Claude widget.

nice, I've built a local banner, but it's hit and miss will try this, love the diet claude @surbhi_singla2

LFG, super useful and needed


Congrats on the launch @surbhi_singla2

Needed something like this so bad.

Congrats on second place with a free Chrome extension. You built it out of your own use case, and you are still calling it v1 on launch day instead of overselling it.

Cool! Can it switch to a different Claude Code license as well? Switching AI providers can sometimes cause issues with understanding context, which could cause problems in some cases.

Hey Product Hunt! Shubham here 👋
Parth and I try almost every AI product we come across (we’re just young curious folks).

And we kept on doing the same thing: a product launched with an insane claim, their agent would feel magical for 10 minutes, then it claimed it completed something it hadn’t, invent a link, or make us repeat ourselves three times.

We’d then message the founders and hear: this is really useful feedback. we had no idea.

And we’d think: wait, you already have the entire conversation & traces. why did we have to tell you?

Turns out, their the AI observability dashboards showed a successful request: 200 OK, tool call succeeded, response generated.

The failure was only visible if someone actually read the conversation. So we built Agnost AI.

Agnost AI reads every production conversation across chat and voice agents. It groups them into recurring failures, behavior drift, hallucinated links, frustration, feature requests and churn signals, with the exact users and conversations behind each one.

From there, you can create an eval, or ask your coding agent to debug the problem & fix it.

Because evals test problems you already know about. You can’t write an eval for something you haven’t discovered yet.

Agnost AI connects in three lines of code or through OpenTelemetry and already analyzes more than one million messages every day.

If you’re running a user-facing agent, connect it. I’ll personally help you find three things happening in your conversations that you probably don’t know about.

Also, how do you currently discover failures your evals don’t cover: user complaints, manually reading traces, or something else?

Can I also save my model inference costs using the insights Agnost gives me?

Congrats on the launch team!!! I played around with the product and it felt super snappy

congrats on the launch! Let's go team.

Been waiting for a product like this. Congrats on the laucnh!

You two kept messaging founders about failures in their agents and kept hearing that they had no idea. Congrats on shipping the version where they find out first, without needing you to tell them.

You noticed that an invented link still comes back as a 200 OK on the dashboard. Congrats on building the thing that actually reads the conversation.

Hey Product Hunt! 👋

When I started Jotform, the goal was simple: make it easier for anyone to collect information online.

But collecting data is only the beginning. The real work often starts after someone clicks “Submit.”

You need to organize responses, find important details, identify patterns, create reports, update records, and follow up with the right people. Too often, that means wrestling with formulas, filters, spreadsheets, and repetitive manual tasks.

Today, we're excited to introduce Jotform AI Data Assistant, an AI assistant that turns form submissions into action.

Instead of navigating menus or building everything manually, simply tell Data Assistant what you need. You can:

📊 Ask questions about your submissions and get clear answers
✨ Identify patterns, recurring themes, and records that need attention
📈 Generate charts, summaries, and visual reports
⚡ Create and organize tables or update multiple records at once
🧠 Summarize, categorize, translate, and enrich data with AI Columns
✉️ Create replies, reminders, and follow-up emails directly from your data

Data Assistant works inside Jotform Tables and Inbox, where your submission data already lives. That means you can move from collecting information to understanding it and acting on it without stitching together multiple tools.

This launch also represents something bigger for Jotform AI.

We’re continuing to expand AI across Jotform, building products that help you not only create faster, but also understand your data, get work done, and take action.

Jotform AI Data Assistant is the latest addition to our growing lineup of AI products, and there’s more on the way. In fact, the next big one is coming soon. 👀

We’d love to hear what you think. Try Jotform AI Data Assistant with your own submissions and let us know:

What would you ask your data first?

This one's pretty cool! Let me just ask some form data questions instead of digging through spreadsheets myself. Great for anyone drowning in form responses who just wants quick insights without the busywork :)

Makes me wonder how well it handles messy open-ended answers, though – not just the neat multiple-choice stuff?

Cool, my friend was asking about a good form solution. Gonna share this with him :)

Congrats 👏

Congratulations 🎊

Turning raw form submissions straight into actionable insights saves a ton of manual spreadsheet sorting. Great build!

You said the real work starts after someone clicks submit, and that is exactly where this one lives. Congrats on the forty ninth launch, which is a lot of shipping for one form builder.

This is launch forty-nine since 2014, and the founder is still down in the thread replying himself. Easy to root for. Congrats on this one.

Hi Product Hunt! 👋

Maker here. Some backstory on why this exists.

My first B2B company was a lead gen product, where I personally onboarded every single customer 1-on-1. My next product was in user onboarding itself (demo videos, similar to Supademo). So I’ve spent years inside this problem: those calls work, but they don’t scale, so most users never get one.

About two years ago, right when GPT-4o came out, I ran an experiment. I gave it a goal inside our app plus a screenshot, and asked for the next step. I performed that step myself, sent it the new screenshot, and asked again. It walked through the entire flow on the first attempt. I hadn’t expected that at all, and it took me a while to realize what it meant: someone was going to use this to replicate those 1-on-1 calls, and that would obliterate the legacy approach of product tours, help docs and tooltip overlays. I figured that someone should be me.

Going from that experiment to an AI that reliably does live screen-sharing calls with real users turned out to be very hard. It took our team 18 months. But it works now: it talks with your users like a human CS agent would, it sees their screen and clicks on things for them, and you add it to your app with a single line of JavaScript. We train it on your product, even on recordings of your past onboarding calls.

The first company running it is growing 40% faster.

Happy to answer anything about how we built this, what broke along the way, or where it's going.

Congratulations on the launch! It's something that I would like to try. Does it know where the payment wall is? What happens with the call when user gets redirected to the payment provider and back? Does it pause and continue when the user returns or does it loose the thread there?

This is going to help a lot to improve new user conversion rates to paid! Can you have complete free-form conversations with the AI? How are you preventing prompt-injections from screen content?

Congrats. I had a chance to try an early version of this product, it's great!

What a cool application of AI. I'm always clicking away launch tours, but this way It can actually help me with what I want to do. Is the idea that it's only there for the onboarding or also for later on in the journey as interactive help functionality

Can it also just literally call my parents?!

Getting closer and closer to Her
(the movie)

Great work, Joris!
Jonno, what a clean and beautiful design 🩵

Joris 💪 Super cool product, man!

That screenshot experiment was two years ago, and it still took your team eighteen months to make it reliable enough to put in front of real users. Congrats on getting it out the door.

Tested a very first version of the product which was already amazing! Excited to see where thinks going

Brilliant stuff. Everything coming from @machielse is something I keep an eye on, and this one really grabbed my attention. Works just great. Can't emphasize this enough. It's amazing how something that's so complex under the hood works so elegantly and smoothly.

Lekker Joris, congrats! Been giving screenshare demos for Salonized myself for years so I get exactly why you built this. Good luck with the launch.

I've given so many product demos over screenshare to small contractors, always walking the customer through it themselves while I explained stuff live. Obviously it converted way better than without, but it ate up a lot of my time.

At the same time, I valued the personal contact. Those calls gave me a ton of feedback on the product itself: hearing what people actually get stuck on, the words they use for their problem, stuff you'd never get from a support ticket.

Nimbia takes that call off your plate, which is great. Curious though how you're handling that feedback loop. When the AI runs the call instead of me, how do I still get that "oh interesting, they always struggle here" insight? Feels like that's the hardest part to replace.

I often send Google Docs with instructions and screenshots, this is the ideal replacement!

Congrats on the launch @machielse. The product looks really helpful and really like the website design.

Wow... this is solving each CS / onboarding painpoint i've ever had in the past. Looks like Nimbia is onto something, awesome to see!

Love this. Product tours were always a poor stand-in for someone sitting next to you, and you're basically putting that person back. Congrats on shipping it, Joris!

Great timing for launching this. Its exactly what we have been looking for. I just signed up and eager to see the demo.

Congrats Joris. Most onboarding tools optimize the top of the funnel. Going after the users who'd normally get a link is the harder and more valuable half.

Excellent launch, Nimbia is really super well rounded up. I love that I can just give all my call transcripts from our previous onboarding calls for Nimbia to learn all about my product, that's really good

Congrats, been waiting to see this ship! The use case I keep comin back to is field teams who barely touch software: site foremen, crop managers, hotel floor staff. What does activation actually look like for someone like that? Does a manager roll it out for the team, or does each user have to set it up themselves?

Very cool! This is going to help to convert a lot more users into paying customers

Can you have a full conversation with the AI? How are you safeguarding it from prompt injections from screen content?

How much space does the data take up? Is it reuploading the photos and videos to the app? I have a lot of media in my Photos app. Could it handle large libraries?

The receipt example sold me, that is the exact search Apple Photos fails at. Doing it fully on device is also the harder engineering path, and the one that means I never have to wonder what a server saw. Where does the offline model start to struggle, handwriting or accents?

honestly, screenshots of text conversations - I take one to remember an address or a plan someone mentioned, then a week later I can't find it because I don't remember which app it came from or what day. video audio search is the feature that would actually solve that for me since half the time it was said out loud, not typed. question on the on-device part: does the model that does the transcription/face recognition ship with the app, or does it pull something down on first launch? asking because I've got an older iPhone and "100% offline" sometimes quietly means "downloads a few hundred MB the first time you open it."

Hey everyone! I'm Anas, the maker of Memoria.

I always found myself scrolling for 10 minutes just to find a specific meme, a receipt, or a video clip of a friend saying a specific word. You know the exact image or video is in your phone, but you just can't find it.

Apple Photos is limited when you want to search for text or audio. Google Photos works, but it requires a monthly subscription and forces you to upload your personal life to the cloud.

I wanted a private alternative. Memoria indexes your camera roll locally.

• On-device AI: It transcribes video audio and reads text in your screenshots. Just type a word spoken in a video or a sentence written on a receipt, and the app finds the media.

• 100% private: Everything runs locally. There is no cloud processing and you don't even need to create an account. Your data never leaves your phone.

• No subscriptions: It's completely free to test on your first 250 media. If you love it, the unlimited version is a one-time purchase heavily discounted for the launch period!

It's free to test on your first 250 media. If you love it, the unlimited version is a one-time purchase, and it's heavily discounted for the launch period!

I will be here all day to answer your questions. I’d be curious to know what is the hardest type of media for you to find in your camera roll right now?

Hey @anasouh , one thing I keep thinking about with local search: if the OCR or the transcription doesn't get a clean read, the media is still indexed, just with nothing useful attached to it. So the user searches, gets zero results, and can't tell whether the media isn't there or whether the text just didn't come through. Have you found a way to surface that difference, or does it mostly not come up in practice?

Looks like we cannot contact you guys : https://www.agentcard.sh/contact

Can multiple agents work on the same project at once while Flare shows their changes separately?

Congrats on the launch!

Love the proposal — I'll run a test on my end and get back to you. It's a great fit for my current use case.

More than an AI setter, a whole AI comercial solution. Amazing work! Lets see the automated CRM running

This looks awesome... what's the one use case that's driven the most revenue for a single client so far? Would love a real example

Hi Lorenzo,

this sounds extremely interesting and useful (and something that could help me cover the part where I, as someone who spent the last 20+ years writing software, suck) - is it safe to use this kind of product in the age where most of the content online is AI-generated and people are very quickly getting sick of seeing the usual AI patterns anywhere?

I am not trying to be annoying, I'd genuinely like to use this kind of product.

the insurance quoting example is a great one — that's a use case where a bad answer is a compliance problem, not just an annoying one. how's handoff handled when the agent isn't confident mid-conversation? still feels like the hard part on multi-channel agents like this

Hi everyone!

Co-hunting something so physically beautiful with @conduit_design.

He called it “the wildest keyboard I have ever seen”🤯

At 4.75mm, Altar II barely looks like a mechanical keyboard. It sits almost as flat as a Magic Keyboard, without the usual height that comes with mechanical switches.

The whole product is built around fitting a real mechanical typing experience into that almost impossibly thin frame. The switches still have 1.8mm of travel, and the engineering gets obsessive enough that even the USB-C housing had to be custom-made because normal ones were thicker than the keyboard.

It’s rare to see a hardware project nail the industrial design and acoustics this well!

Hi everyone, I'm Andrew, the creator of Altar II.

Altar II is an ultra-low profile (4.75mm) mechanical keyboard designed to replace your Magic Keyboard. It's the keyboard I wish Apple made.

It has fully mechanical switches with 1.8mm of travel, a magnetically detachable dial, haptic feedback, a red backlight, a speaker, and a native macOS companion app. The chassis is a single piece of CNC-machined aluminium.

I'm a heavy Mac user and I feel Apple hasn't given its keyboards the attention they deserve in terms of hardware, software or features, so I set out to change that. It has taken almost two years. The hardest parts were fitting a reasonably sized battery into the chassis and getting the power profiling right without touching the typing experience. There was also literally no space on the underside of the PCB, so every component had to go on top. Even the USB-C housing is custom because a standard one is thicker than the keyboard.

I've taken a lot of the feedback from our first keyboard, Altar I, and incorporated it into Altar II, including the detachable dial and pairing button placement.

Reservations are open now ($1 locks in the $249 price, against $349 retail). Kickstarter launches 10 November 2026.

At 4.75mm it is actually travel-viable. My current keyboard is a small brick that never leaves the desk. Question on the companion app: how much of the dial and haptic customization lives in app versus firmware? Asking because I want to know if my setup carries over on a second Mac or if I start from scratch each time.

Will this be available in ISO format at any point?

How does it sound when someone is typing? 👀

A 4.75mm mechanical board is a compromise I did not think was possible. My Magic Keyboard is flat and lifeless, and every mechanical I tried sat on the desk like a brick. Did the short travel keep a real bottom out, or is that the tradeoff?

Keeping a site current is always the thing I quietly postpone because it means dropping what I am doing to go fiddle somewhere else. Doing it right where the writing already happens sounds calm and sane. Nice work Taqib.

congrats on shipping this solo, the "zero Electron" framing is doing a lot of work and honestly for a file manager it should - I've quit using more than one "modern Finder" alternative purely because it lagged scrolling a folder with a few thousand files. curious about the SFTP/SMB piece though - when you save server credentials, are those going into the macOS Keychain or do you roll your own storage for that? that's usually the detail that decides whether I trust a new file manager with my actual server logins or just use it for local stuff.

Hey @mnemosynee Martin, I have quietly resented Finder for years and long since stopped expecting better, so watching someone finally give it a proper rival feels good.

Hey Product Hunt 👋 I'm Martin, the solo developer behind DockDuck.

I've lived on a Mac for years, and Finder always felt… stuck. It barely changes, and every "alternative" was either a powerful-but-dated power tool, or an Electron app that ate my RAM and battery just to list files.

I wanted something that felt like Apple made it — fast, native, genuinely beautiful — but with the power features I actually reach for: dual-pane, connecting to servers, batch rename, tags, and a pinned dashboard for the stuff I open every day.

So I built DockDuck. 100% Swift and AppKit, zero Electron. It opens instantly, stays out of your way, and your files never leave your Mac. And it's pay-once (or yearly) — no subscription, because I'm tired of those too.

It's a free 14-day Pro trial, no card needed. And for the PH community, PRODUCTHUNT21 takes 10% off any plan until Sept 30.

This is an early launch and I'm building it in public. I'd genuinely love your feedback on what would make DockDuck your daily file manager — and I'm happy to talk about how it's built, the design decisions, any of it. 🦆

I love that it shows conflicting shortcuts too! Does it work across most common apps?

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Upload an image. Customize the particles. Add motion. Make it interactive. 🚀

@zayne_zhang nice! how do you differ from the competitors in this space right now? Might check out a demo

i like the combination of identifying and fixing at the same time

this is a real gap - I've had the "what did we decide about X" problem plenty of times across long-running Claude Code sessions. Curious how it behaves for a monorepo setup where frontend and backend live in separate directories but are logically one project - does the per-project indexing stay strictly siloed to each directory, or is there a way to point it at a shared index across a few related repos?

Hi,

Head of the Buddy QA team here. We’re running a couple thousand Playwright tests that cover pretty much the entire platform.

Adding Visual Tests on top of that gives us another layer of confidence. Playwright tells us whether everything works as expected, while Visual Tests help us catch layout shifts, styling issues, and other visual regressions that can still slip through a passing test suite.

For us, it fits naturally into the QA process we already had in place rather than replacing anything.

Hi, 

Head of the Buddy frontend team here. Most of our frontend workflow already exists in Buddy: building Storybook, unit and e2e tests, preview environments (sandboxes) and automation. The only thing we had to do externally was visual regression. 

Now every change runs against approved baselines and visual diffs across the component library get flagged automatically. Each run also publishes a hosted Storybook preview for the branch, which is handy when a diff needs a second pair of eyes.