Founders waste days building startup ideas before discovering prior failed predecessors, while existing AI discovery tools hallucinate fake source URLs and fail on niche or open-source software categories.
Founders waste days planning or building startup ideas before discovering prior failed competitors, while AI tools built to solve this suffer from hallucinated source URLs and poor categorization accuracy.
I built a tool that tells you who already tried your startup idea, and how they died
the source URL for all 5 of the corpses were fake. I've hit this issue before myself when asking an AI to back up its answers with sources.
commentInteresting idea. But the source URL for all 5 of the corpses were fake. I've hit this issue before myself when asking an AI to back up its answers with sources. It just takes a real domain and then appends a generated path which matches the desired topic.
Neat idea, but doesn't work as well for FOSS projects.
commentNeat idea, but doesn't work as well for FOSS projects. Tried: free, open source, photo blog. Only one it got right was Pixelpost. Missed Greymatter entirely. Wordpress is still standing although not strictly a photo blog. Most of the products it returned are photo galleries, not photo blogs.
Solo founders and software engineers actively brainstorming or scoping new micro-SaaS and dev-tool projects.
Repeated complaints about wasting days before finding dead predecessors and current AI tools generating fake, hallucinated source URLs.
Guaranteed zero-hallucination source links combined with specialized search over open-source (FOSS) and tech startup graveyards.
A niche prior-art research tool that searches verified historical startup databases (YC Graveyard, Crunchbase, GitHub, Product Hunt) and verifies every single URL before presenting grave reports.
Founders waste hundreds of dollars in billable dev time building dead ideas; paying $29 to instantly avoid 3 days of wasted work provides an obvious ROI.
“Discover dead predecessors and past startup graves in 60 seconds with 100% verified URLs.”
A niche prior-art research tool that searches verified historical startup databases (YC Graveyard, Crunchbase, GitHub, Product Hunt) and verifies every single URL before presenting grave reports.
Launch on Hacker News ('Show HN'), Product Hunt, and Indie Hackers with free public autopsy reports of famous startup failures.
Validating Wayback Machine snapshots and domain availability in real-time can slow down report generation.
Users may subscribe for one month, research their immediate idea, and churn until their next project.
Missing obscure GitHub repositories or defunct self-hosted open-source software tools could harm user trust.
Run an Investment Memo to get a structured Go / No-Go verdict, competitor landscape, unit economics, and a 90-day validation roadmap for this opportunity.
Generate an investment memoThis idea scores in the upper-middle range of opportunities surfaced by MonetScope, with a validation sub-score of 8/10 against 3 independently sourced evidence signals. A "promising" rating usually indicates a real pain has been detected and discussed in the open, but the pipeline did not find enough signal to flag it as urgent or high-frequency. These opportunities can still produce excellent businesses — they often correspond to "boring" problems that established players have ignored — but the founder should expect a longer customer-development cycle to confirm willingness to pay.
It sits at the intersection of "ai-powered", "automation", "creators", which makes it relevant to a specific subset of founders rather than a generic horizontal opportunity. SaaS opportunities at this stage tend to win on the strength of their initial wedge — a single workflow that the target user runs every week, where the existing solution is either spreadsheets, a clunky incumbent feature, or a manual process they hate. The build cost is moderate; the distribution cost is everything. The MonetScope pipeline surfaces this category alongside other saas signals, which is why it appears here rather than in a generic "trending ideas" feed.
Scores are derived from real forum discussions across Reddit, Hacker News and X, weighted by evidence volume and signal quality. How scoring works
MonetScope does not generate ideas from a language model's imagination. Every opportunity on this site is anchored to specific source posts and comments from real public discussions — typically on Reddit, Hacker News, or X — where actual users describe the pain in their own words. The AI's role is structuring, scoring, and grouping those signals into a navigable opportunity, not inventing the problem.
MonetScope's spider pipeline runs continuously and surfaces opportunities as new evidence accumulates. The "Updated" date in the header reflects the most recent re-scoring of this specific opportunity. Most saas opportunities visible in the public catalog draw from discussions in the last 30-60 days; older signals are de-prioritized because user pain shifts faster than most founders assume.
Overall score is a composite across six dimensions — pain, urgency, willingness to pay, market size, defensibility, and execution ease — designed to give a single number for triage. Validation score is narrower: it asks "how cleanly does the same signal repeat across independent sources?" An opportunity can score high on overall but lower on validation when one or two large discussions dominate the evidence; conversely, validation can be high on a smaller-overall idea where the signal is consistent but the addressable market is modest.
