One recurring piece of feedback after launching PH Radar was that makers want more context, not just rankings.

I'm currently experimenting with a BI layer that analyzes Product Hunt activity beyond the daily leaderboard.

Current prototype dashboards include::

Launches by category
Votes by category
Hunter activity
Comment-to-vote ratios
Historical launch trends

https://www.producthunt.com/prod...

It's the end of the month. Your client needs a performance report, so you open five tools, screenshot the numbers, paste them into Google Slides, and spend two hours making it look like you didn't just paste screenshots into Google Slides.

We just made that whole process unnecessary.

AI is a great, cheap foundation we can all agree on that (depending on token usage, of course).

When you re building your first product, and you re not sure if it will work and earn money, the obvious goal is to keep costs as low as possible and avoid burning money early on.

What started as a Product Hunt companion has become a BI layer for launches.

Custom dashboards, momentum, opportunity radar, hunter analytics, repeat launches, race replay, maker responsiveness and more.

Special thanks to @oshylabs and everyone in this forum whose feedback shaped a lot of this repeat launches and the responsiveness signal came straight out of conversations here. (The responsiveness metric even caught a question I'd missed on my own launch.)

What's still missing? If you could add one metric to Product Hunt itself, what would it be?

Six years ago I got into Y Combinator and built the first version of @Basedash: AI data analyst. It was a simple tool that let you edit data in your database.
Now, six years later, we have a whole new product, and again we're shipping... database editing. But this time it's a look into the future of how companies are going to be run.
At the surface, this feature is kinda neat but nothing new. You can ask the Basedash AI to edit things in your database or call MCP servers to take action in other tools.
But, being a BI product, Basedash has a super deep understanding of your business. Probably better than you do yourself.
Soon, Basedash will proactively start suggesting ways to make your business better.
"If you extend this user's trial, they'll have a 50% higher chance of converting"
"If you tweak your ad sequence with this copy, it'll increase conversion rate by 20%"
One click to approve and run the experiment.
This is how we transition to AI-run companies.

Please check out our PH launch for actions and give us any support or feedback: https://www.producthunt.com/prod...

We've been thinking a lot about this moment. A stakeholder asks "how did our paid campaigns do last week?" or "are we on track for the month?" - and even with dashboards already built, getting a clean answer still takes more steps than it should.

You open the right tool. Filter the right date range. Cross-reference another source. Paste it into a Slack message. Sometimes you just end up saying "let me get back to you on that."

The data exists. The dashboards exist. But the path from question to answer still has too much friction in it.

That's the problem we set out to solve with Databox MCP - launching on Product Hunt May 28. Instead of navigating dashboards, you ask the question directly in whatever AI tool you already use - Claude, ChatGPT, n8n, Cursor - and get an answer pulled from your live data.

There's never been a better time to build. AI tools, smaller teams, faster product cycles.

Last year, @Supabase surveyed over 2,000 startup founders and builders to uncover what's powering modern startups: tech stacks, GTM, and approach to AI.

Many things have changed since then, and they want to know what building at startups looks like in 2026.

We ve been growing really fast (30%+ MoM ARR) at @Basedash since launching last year. Most of that growth has been the result of hard work, but we ve also had a secret weapon: an AI agent that acts as both a data analyst and a PM, working 24/7 to optimize our product s activation and conversion rates.

For decades, companies have been making product decisions based on intuition and manual data analysis. We wanted to see what would happen if AI could take the wheel completely.

We ve been growing really fast (30%+ MoM ARR) at @Basedash since launching last year. Most of that growth has been the result of hard work, but we ve also had a secret weapon: an AI agent that acts as both a data analyst and a PM, working 24/7 to optimize our product s activation and conversion rates.

For decades, companies have been making product decisions based on intuition and manual data analysis. We wanted to see what would happen if AI could take the wheel completely.

Supabase recently surveyed over 2,000 startup founders and builders to uncover what's powering modern startups: tech stacks, GTM, and approach to AI.

See full report here

Hey everyone -

I m the founder and CEO of Metabase and I m here to shill our upcoming launch of our Embedding versions. 

Hey everyone -

I m the founder and CEO of Metabase and I m here to shill our upcoming launch of our Embedding versions. 

We've all been there drowning in dashboards, buried in Notion docs, pinged in Slack threads, and still no clarity. As someone who's spent years working in ops and product, I'm constantly surprised at how hard it is to get a clean, real-time picture of what's actually going on in the business.

Why do we still need 4 tools and 5 people to answer simple questions like What s driving churn? or Are we hitting our sales targets?

Curious how others are thinking about this. If you're an operator, PM, or founder how are you solving this internally? Have you found workarounds or is it still duct tape + gut feeling?

The other day I saw a poll on LinkedIn which said one of the biggest ongoing struggles of startups and small businesses is reliable, scalable lead generation especially beyond the usual tools like Apollo, ZoomInfo, Clearbit, etc.

Product Hunt often features some fresh and creative approaches to data. I have seen some around company enrichment, contact intelligence, trigger signals or even outreach automation.
But often PH launches get forgotten after their launch day.

What are some lesser-known or recent data tools you ve come across on Product Hunt that help with lead gen, enrichment, or prospecting?