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Clinical-grade health data processing

exora uses a multi-pass AI pipeline to go beyond simple text extraction - understanding the clinical meaning of your health documents.

The pipeline

1

Document analysis

exora identifies the type of document, the healthcare provider, and the date of the encounter. OCR is applied to scanned or photographed documents.

2

Entity detection

Clinical entities are identified across the document - conditions, medications, vitals, lab results, procedures, allergies, immunizations, and more.

3

Clinical extraction

Detected entities are extracted into structured clinical data. A single document can produce dozens of structured health facts, each linked to its exact location in the source.

4

Medical coding

Extracted entities are mapped to international medical coding standards - SNOMED CT for conditions and procedures, RxNorm for medications, LOINC for lab results. This gives your data clinical precision and interoperability.

5

Unified health record

All extracted data is merged into your health profile, deduplicated, and organized. Your complete health picture, built one document at a time.

Built with the best AI available

exora uses Google Gemini and OpenAI models - selected for each stage of the pipeline based on accuracy, speed, and cost. Under our commercial API agreements, your health data is never used for AI model training.

Every fact has a receipt

This is not a black box. Every piece of extracted health data maintains provenance - a link back to the exact document, page, and text it was extracted from. You can verify anything, anytime.

AI is a tool, not a doctor

exora organizes and presents your health data. It does not provide medical advice, diagnosis, or treatment. AI extraction may contain errors. Always consult a healthcare professional for medical decisions, and verify AI-extracted data against your source documents.

See it in action

exora is currently in private early access (invite code required).

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No invite code? Request early access