SignalScout AI: Evidence-First Why-Now Engine

SignalScout AI is an evidence-first why-now engine for GTM and sales teams. Sales reps often spend hours researching accounts, but still reach out too late, with generic messaging and black-box intent scores. SignalScout answers one practical question: why should we contact this company right now? The system uses Bright Data as the live public-web data layer. SERP API collects fresh news, funding, product, and competitor signals. Web Unlocker extracts full text from hard-to-access pages. Web Scraper API provides pre-warmed hiring snapshots for directional hiring evidence. The backend then converts these signals into typed evidence rows with source URLs, source tiers, confidence, mode labels, and a reproducibility hash. Unlike typical AI sales tools, SignalScout does not let the LLM generate numeric scores. Scores are computed deterministically in Python from explicit signal weights, impact, confidence boost, and mode multiplier. Claude Haiku is used only for evidence-grounded synthesis: executive summary, why-now reason, sales angles, cold email, LinkedIn message, and discovery questions. The product is deployed as a live cockpit on Vercel with a FastAPI backend on Google Cloud Run. Each run shows the agent pipeline, evidence ledger, scoring audit trail, Bright Data infrastructure usage, and action pack. The result is a sales-ready GTM brief that is live, deterministic, and traceable.