MedHub AI Lab
A privacy-first lab-report organiser that turns PDFs, photos, and scans into a reviewable health timeline, with personal-data controls before anything is saved.
What it helps with
Lab results arrive as PDFs, photographs, scans, and printouts from different clinics, often using different languages, abbreviations, and layouts. Patients are left with a collection of documents that is difficult to organise or compare across visits, even before they decide which personal details they are comfortable storing.
What was built
The product flow accepts a report as a PDF, photo, or scan, extracts and normalises the measurements, and highlights names, identifiers, addresses, and other possible personal data before storage. The person can correct the extracted values and decide what to keep or redact. Once confirmed, results join a timeline where values can be compared across visits and given context through notes, symptoms, or medication information. The product is designed around portable records and data-residency choices rather than dependence on one processing provider.
What made it different
MedHub AI Lab puts control at the two moments where health-data tools often remove it: interpreting the document and deciding what becomes part of the record. The original report, proposed values, and detected private details stay visible before saving. That makes the product an organiser for a person’s health journey, while medical interpretation and clinical decisions remain outside its role.
People should review both the extracted values and what stays private before a health record enters their history.
What it demonstrates
- Lab-report upload across PDFs, photos, scans, languages, and formats
- Personal-data review, correction, and redaction before saving
- Trends across visits with notes and portable records