Surface recent Reddit/forum threads where users ask for apps like yours (automated discovery)

Executive Summary

Many small teams, indie‑SaaS founders, and product marketers struggle to find clear, timely intent signals on Reddit, Discord, and StackExchange because manual monitoring is noisy and keyword matching misses colloquial phrasing. This is a meaningful problem in a $3.6B market (roughly 600,000 businesses at a $6,000 ACV) where discovery tools can materially impact acquisition and product feedback. You could build an automated discovery service that continuously surfaces recent forum threads where users explicitly ask for apps like yours, combining semantic embedding search, intent classification, freshness scoring, and filters for category, geography, and company size. Integrations would push high‑confidence leads into Slack, CRMs, or outreach templates, with a freemium tier for solo founders and enterprise plans (compliance, rate‑limit handling, SLA pipelines) targeting higher ACV customers. The technical core would rely on modern embedding models to detect intent across short, colloquial posts rather than brittle keyword lists. The timing is favorable—market score 92/100 and revenue potential 78/100—because indie‑SaaS growth, community‑driven acquisition, and advances in embedding search are converging to increase demand for intent‑surfacing tools. Differentiation will come from honest tradeoffs: strengths include better signal‑to‑noise through intent scoring, vertical taxonomies, and tight workflow integrations, while real challenges are forum API access, moderation and privacy risks, and the engineering effort to tune relevance so the product helps rather than annoy community users; if you can solve those, this is worth pursuing in a medium‑competition landscape.