WebScout

WebScout is a self-improving web scraping agent that learns from every success and failure. Traditional scrapers break silently when sites change and repeat the same mistakes. WebScout solves this with a 6-stage learning loop: it searches a vector cache for patterns that worked on similar pages, reuses high-confidence matches instantly, or extracts fresh data with GPT-4o and Stagehand. Failed extractions trigger four recovery strategies including autonomous browsing and cross-model Gemini analysis. Every successful pattern is stored as a vector embedding for reuse, and every step is traced through Weave. The result is measurable improvement: cache hits climb from 14% to 83%, speed improves 3.7x, and success rates reach 100%.