Historify

Most people's medical history is a pile of PDF lab reports — one per clinic, each in its own layout, none of them talking to each other. A single value tells you almost nothing; the trend across all of them tells you everything, but nobody ever gets to see it. Historify turns those scattered PDFs into one structured, longitudinal health record. Upload a report and Claude reads it page by page, extracting each marker with a confidence score, while a deterministic backend normalizes units and reconciles results across labs — reconstructing a trajectory that no single exam, and no single clinic, could ever show. Low-confidence readings are flagged and linked to the exact source line: the AI is allowed to be uncertain, and the person stays in control. Any marker can be traced over years, or exported as a one-click report to share with a doctor. Built from scratch during the hackathon, Historify's real finding is a design principle: the hardest part of a health record isn't intelligence — it's trust, and trust comes from traceability. Claude reads, the backend calculates. It never diagnoses.