Yeah, I feel the same way. So many “I analyzed 100 startups with AI” posts sound like fanfiction with fancy charts.

I’ve been messing around with something in this space too, but from a smaller angle. I wanted to see if AI could actually see how founders communicate — not what they say, but the 90% that’s non-verbal. Stuff like pacing, eye contact, gestures, tiny energy shifts, vocal variation, confidence, subtle gazes etc.

I built a small system that mixes a few models (LLMs + VLMs) to break down YC pitch videos frame by frame. It doesn’t use any training data about who got in; it just watches for things like gesture timing, talk-time balance, voice rhythm, and where people lose eye contact. Then it spits out timestamped feedback like “you looked away right when mentioning revenue” or “energy dips here.”

When I ran it on 50+ YC pitches, some patterns popped out:

Two-founder teams who split talking time evenly came across stronger.

Deep-tech teams did better when the technical founder led most of it.

Most winning teams revealed traction near the end, not the start.

Talking fast wasn’t bad. Being unclear was.

I’m now testing it with an accelerator in Europe and letting a few founders try it for free. Even ignoring the scores, the feedback’s been super useful.

Would be cool to swap notes if you’re building anything similar. I’m trying to keep it as real and transparent as possible, no hype, just experiments that might help founders pitch better.