TL;DR: PainHunt is a research tool that pulls real user complaints from 24 public platforms, scores each one with AI for how painful it is and how much commercial potential it carries, and lets you search them. The point is simple: build something people already complain about, not something you hope they want.
What problem does PainHunt solve?
Most startup ideas fail for one boring reason — nobody needed them. The usual fix is "talk to users," but before you have users, you're guessing about which problem to even chase.
There is, however, a massive public record of problems people already have: Reddit threads, Hacker News comments, one-star App Store reviews, GitHub issues, Stack Exchange questions. The signal is there. It's just scattered across dozens of platforms and buried under noise.
PainHunt's job is to collect that signal in one place and rank it, so the question shifts from "what should I build?" to "which of these well-evidenced problems is worth solving?"
What exactly is PainHunt?
It's three things working together:
- A crawler network that continuously collects public posts from 24 platforms — Reddit, Hacker News, the App Store and Google Play (across many countries), GitHub Issues and Discussions, Stack Exchange, Product Hunt, and more.
- An AI pipeline that reads each post and extracts the underlying pain points, then scores them — intensity on a 0–10 scale, and commercial potential on a 0–15 scale that factors in willingness to pay.
- A searchable app where you filter by keyword, platform, or category and read concise summaries instead of trawling raw threads yourself.
As of this writing the system has analyzed 488,000+ real user posts. The result is a database of problems, each one tagged, scored, and linked back to its source.
What can you actually do with it?
- Search by problem space. Type a keyword or category and see what people complain about most intensely.
- Sort by commercial potential. A loud complaint isn't always a business. The score helps separate "annoying" from "people would pay to fix this."
- Validate an idea you already have. The Idea Validator scores your concept against the real demand evidence in the database.
- Study competitors' weak spots. Reviews and threads are full of "I wish [product] did X" — exactly the gaps a new entrant can target.
What PainHunt is not
To be accurate about scope:
- It is not a guarantee. A high score means strong evidence of a problem, not a promise that your execution will work.
- It is not a scraper you point at one site. It's a curated, scored dataset across many sources.
- It does not republish original content. You get AI summaries and a link back to the public source, never the original author's full text.
How does it compare to just searching Reddit yourself?
| Manual research | PainHunt | |
|---|---|---|
| Coverage | One platform at a time | 24 platforms in one place |
| Scoring | Your gut | AI scores for intensity + commercial potential |
| Time per idea | Hours of reading | Minutes of filtering |
| Bias | You see what you search for | Surfaces problems you didn't think to look for |
Manual research is free and still valuable for depth. PainHunt is about breadth and ranking — getting from "no idea" to "ten evidenced candidates" quickly, then going deep on the best one.
Where to start
If you're exploring, open the Pain Point Browser and search a domain you know. If you already have an idea, run it through the Idea Validator. For the full mechanics, read how PainHunt works.