I’m Lu. I spent the last year falling into the classic trap: building solutions first, then looking for problems. After launching two projects that got zero traction, I realized I needed to validate demand before writing code.

I started manually browsing subreddits like r/SaaS, r/marketing, and r/smallbusiness, looking for posts containing phrases like "how do I," "why is X so hard," or "I hate Y." It worked, but it was unscalable.

So, I automated it. I built Nichestarter.ai.

How it works (The Stack):

Ingestion: I try to scrape daily threads from high-signal subreddits (and soon G2 reviews).

Filtering (The hard part): I run raw posts through a cheaper model to filter out noise, general questions, and low-effort rants.

Analysis: Valid complaints are passed to llm to analyze "Willingness to Pay" (based on sentiment and business context) and "Solution Complexity."

Matching: I built a match engine that pairs these problems with user skills (e.g., "React Dev" + "Marketing Pain Point").

The Result: A daily feed of "Gap Analysis." Instead of just seeing a Reddit post, you see the core pain point, the customer segment, and a generated MVP roadmap.

It’s currently in beta. I have a free tier that sends a weekly digest of the best opportunities found.

I’d love to hear your feedback on the matching logic—specifically, does the "Opportunity Score" feel accurate to you?

Thanks!