ExtractQ cuts auto-insurance claim time 75% with zero-training AI

Show HN: ExtractQ cuts auto-insurance claim time 75% with zero-training AI

ExtractQ cuts auto-insurance claim time 75% with zero-training AI is active in the show hn launch space.

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Hi HN—Berwin here.We built ExtractQ after watching friends in insurance re-type PDFs all day. The service uses a vision-plus-LLM pipeline (AWS Bedrock + LangChain + CrewAI) to map any incoming doc to JSON without per-form training. We then validate via third-party APIs (DMV, VIN) before ingesting into the core claims app.In production at a mid-size insurer we cut average claim prep time from 45min to 19min and reduced downstream data-entry errors by 85%.I’d love feedback on scaling doc-heavy AI workflows—especially around validation and audit trails.

Within the show hn launch space, the company focuses on its core offering rather than a broad product line.

It is recorded at the Show HN launch stage.

Website: www.scalong.com/case-studies/revolutionizing-auto-insurance-claims-with-processq