Building a 14-County Real Estate Data Pipeline with CrawlOS and Supabase: Automating Lead Scoring at Scale

At Load Bearing Capital, we process hundreds of property records across the Houston metropolitan area every night—automatically. This article details how we integrated CrawlOS into our Supabase infrastructure to build a horizontally-scaled web scraper covering 14 counties, generating ~125 qualified wholesale leads per nightly run using pg_cron automation. We'll walk through our schema design (17 normalized tables), the lbc-hcad-actor deployment pattern, and how we structured real estate data pipelines to support both StructCalc AI's structural analysis and Load Bearing Capital's acquisition strategy—all running on self-hosted infrastructure with zero external data vendor dependencies.