I spent 3 months building an AI idea validator. Here are the first 49 real data points (and the hardest lesson I learned).

If you are like me, you’ve probably asked ChatGPT to validate your startup idea.

The response is always some variation of: “This is a promising market, but you need to validate demand.”

It sounds smart, but it’s completely useless. It’s just an AI guessing based on its training data. It doesn’t tell you if real people are actually complaining about this problem today.

I got tired of this, so I built Ainexa — a startup idea validator that doesn't guess. It scans live data sources (Reddit, Hacker News, Product Hunt, etc.) and forces the AI to link every claim to a real, clickable source.

My Rule: If we can't find evidence for a claim, the AI is not allowed to make it up.

Over the last few months, I’ve been building this in public. I’ve run the first batch of 49 real ideas submitted by early users through the system.

Here is what the data actually surprised me with:

1. “AI Wrapper” ideas are getting slaughtered
   Out of the 49 ideas I scanned, the ones focused on generic “AI + [Something]” had the highest competition scores and the lowest overall viability. The market signal was weak. It’s not that AI is dead, it’s that the “thin wrapper” era is over.

2. Specificity equals demand
   The ideas that scored the highest had extremely specific target users. For example, an idea targeting “freelance illustrators who invoice in multiple currencies” scored much higher than a generic “invoicing tool for small businesses.” The narrower the niche, the stronger the community signals we could find.

3. The "Zero Competitor" trap
   One user submitted an idea and proudly said, "There is zero competition for this."
   Our system scanned the web and found 4 indirect competitors. But more importantly, it found zero demand signals. No one was complaining about this problem.

No competition usually means no market. You want competitors; it proves people are willing to pay.

The hardest lesson after 3 months
Building the scanning logic was hard. Making the AI perfectly cite its sources without hallucinating was even harder.

But the hardest part? Distribution.

I have 0 paying users. I have the tool, I have the data, but getting people to see it is a completely different game.

What’s next?
I am opening Ainexa to the first batch of early adopters on DEV. If you have an idea you are chewing on right now, let me help you verify it.

You can drop your idea in the comments below, and I will run it through Ainexa for free and reply with the actual data and sources it finds. No strings attached.

If you want to run your own scan, you can try it here: https://www.ainexa.xyz/ (Use code DEV50 for 50% off if you want the full report).

I’m building this in public. If you have feedback on the UI, the data, or just want to tell me I’m wrong, my inbox is open.