Building Verdict AI — a market-signal driven way to kill bad startup ideas early (feedback wanted)P
Hey Indie Hackers đź‘‹
I’m building Verdict AI in public and would love honest feedback.
The idea came from a pattern I kept seeing (and repeating myself): spending months building products only to discover the market didn’t care. Not because execution was bad — but because validation was shallow or skipped.
Verdict AI isn’t meant to be an oracle or a “gu replacement.” It’s an early risk filter. You input a startup idea and it synthesizes market signals — demand, competitors, pricing signals, and repeated pain points from places like Reddit & HN — then explains where the idea breaks and why it should pivot (or if it’s worth pursuing).
The most important output isn’t “go / kill” — it’s the reasoning behind a pivot and what’s missing.
I’m still shaping:
How much weight to give noisy community signals
How to explain confidence vs. uncertainty clearly
Where this fits in a founder’s workflow (pre-MVP, post-MVP, or both)
I’d really appreciate:
Feedback on the concept
Pitfalls I should watch for
How you personally validate ideas early
If anyone’s open to reviewing a sample report or sharing how they’d use (or not use) something like this, I’m all ears.
Do check it out at https://getverdictai.com
Thanks 🙏
The "early risk filter" framing is smart — not trying to replace founder judgment, just surface signals that are easy to miss when you're emotionally invested.
A few thoughts on your open questions:
Noisy community signals: The challenge isn't just noise — it's recency bias. Reddit/HN discussions from 2 years ago might be outdated (market shifted, competitors emerged, tech changed). How are you handling temporal weighting?
Confidence vs uncertainty: One thing I've seen work is separating "signal strength" from "verdict confidence." Strong signal (lots of discussion) doesn't always mean high confidence (especially if sentiment is split). Showing both independently might help founders calibrate.
Where in the workflow: My guess is pre-MVP is where you'd get the most usage, but post-MVP feedback (why users churned, what they actually wanted) is where the real value compounds. If you can connect early validation to eventual outcome data, that becomes a moat.
Pitfall to watch: Founders might use a "go" verdict as permission to skip customer conversations. The tool could actually increase shallow validation if positioned wrong. Maybe worth framing it as "here's what you need to investigate further" rather than "here's the answer."
Curious — does the report include actionable next steps, or is it purely analysis?