SignalWindow: GTM Intent Radar

GTM teams lose deals because the strongest buying signals never make it into their stack. Churn threads on Reddit, pricing complaints on Hacker News, and switching intent on G2 sit behind bot protection, JavaScript rendering, and rate limits—so RevOps and AEs research manually and still miss the window. SignalWindow is not a chatbot. It is a closed-loop intelligence pipeline built for the Bright Data hackathon. For each watchlist company, Bright Data SERP API discovers what changed (pricing, careers, changelog, community queries). Web Unlocker and Browser API extract blocked pages as markdown with source URLs and timestamps. A deterministic Window Score ranks winnability in Python; AI/ML API only explains why—never inventing the score. Cognee plus Redis remember signals across runs so context compounds. When the score crosses threshold, TriggerWare or Slack delivers an action-ready brief with outreach draft. The Streamlit demo runs end-to-end in demo mode with pre-cached extracts, or live against real Bright Data endpoints. Toggle “Simulate change” to inject a synthetic churn signal, watch the diff fire, score jump, and alert execute on stage—proving Discover → Extract → Score → Reason → Remember → Act in under five minutes. We surface buying intent before it appears in ZoomInfo or Clearbit: evidence-grade, cited, and automated. Bright Data unlocks the web; SignalWindow turns it into GTM action.