Collect public events
We collect public product events from Product Hunt, GitHub Trending, Hacker News and selected Reddit communities. Every public item keeps its original attribution and outbound source.
Methodology
How ProductSignal turns noisy events into product intelligence.
ProductSignal is a research surface for indie builders. It is not a recommendation list, investment ranking or substitute for independent due diligence.
Resolve product entities
Different links, launches and discussions may refer to the same product. We normalize them into canonical product entities so repeated appearances can be compared over time and across ecosystems.
Enrich and classify
Products receive bilingual summaries, categories, tags, source history and optional RepoDaily deep-dive links. Automated enrichment supports research; it does not replace source evidence.
Compare repeated signals
Cross-source appearances, active days, event counts and category concentration are more useful than a single ranking spike. Future Topics and Weekly views will expose these patterns more directly.
Public boundaries
What the site deliberately does not claim
Not an endorsement
Appearing on ProductSignal does not mean a product is safe, reliable, commercially viable or suitable for a specific use case.
Needs collection is retired
The Reddit demand-extraction method was not reliable enough for product research. ProductSignal no longer collects, translates, enriches, ranks or publishes Needs; historical files remain audit-only.
No hidden ranking score
We prefer visible evidence such as sources, dates, active days and repeated appearances over an unexplained composite score.
No live LLM calls during site build
Language and semantic enrichment are prepared before the static Astro build. Cloudflare Pages builds only the committed site data.
Current product surfaces
Overview → Explore → Curated → History
Overview summarizes recent activity. Explore exposes the canonical product database. Curated keeps a small set of editorial picks. History preserves date-based audit trails.
Topics now exposes high-quality opportunity clusters and lifecycle states. Weekly summarizes watchlist, rising, cooling and crowded themes from the same cluster and weekly datasets.