Medikeep turns scattered reports, scans, and prescriptions into a local-first medical archive. It preserves the original source file, separates reports from prescriptions, tracks symptoms, and lets you connect records into care histories without editing a wall of OCR text.
| Measurement | Value | Unit | Range |
|---|---|---|---|
| HbA1c | 5.7 | % | 4.0 – 5.6 |
| Estimated Average Glucose | 117 | mg/dL | — |
| HDL Cholesterol | 37.6 | mg/dL | > 40 |
Families accumulate prescriptions, test reports, and scans across years. Most files are visually readable but structurally useless, especially when they come from different labs and different layouts. Medikeep keeps the file, extracts what matters, and still lets the user check the source.
Bring in machine-generated PDFs, scanned reports, prescription images, or plain text and keep the original file archived inside the app.
Medikeep keeps document types distinct so imported reports and prescriptions do not collapse into one mixed archive.
Connect prescriptions, reports, and symptom history into a care journey while keeping each source visible and reviewable.
The workflow is designed around inconsistent lab layouts, mixed-quality scans, and the fact that health data should remain reviewable, linkable, and user-controlled.
The source file is copied into the app’s private archive so the document is still available for verification later.
PDF text extraction is preferred when available; OCR is used for scans and images when the document lacks a reliable text layer.
Reports and prescriptions are stored separately, while medical terms are grouped into readable sections such as Blood sugar, Cholesterol, Thyroid, and Blood count.
The user can compare the structured output against the original file, fix specific rows, and link symptoms or follow-up records into a care track.
Medikeep is being built as a real personal records layer: original document preview, structured rows, editable corrections, symptom tracking, and an offline-first default for sensitive data.
Medikeep is currently being developed as an Android-first medical archive with structured parsing, separate report and prescription views, symptom tracking, care-track linking, and source-preserving imports.