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Notora MedThe voice of records

How it works.

A pipeline built around the expert's signature, not in place of it.

See a worked example →

  1. 01

    Bundle uploaded.

    You upload the medical records bundle as PDF. Encrypted in transit using TLS 1.3, encrypted at rest using AES-256 via AWS Key Management Service. Processed in the AWS London region (eu-west-2). No data leaves UK soil.

  2. 02

    Optical character recognition.

    Every page is read, including handwritten GP notes. Each extracted character carries a confidence score. Low-confidence segments are flagged for review, never silently corrected.

    aBc?d

  3. 03

    Structured timeline.

    Every dated clinical encounter becomes a discrete event with structured fields: date, location, clinician, presenting complaint, examination, investigations, treatment, disposition. Verbatim extract attached. Source page attached.

  4. 04

    Comorbidity context.

    Pre-accident baseline. Relevant comorbidities for the claim region. Medication history. Prior similar claims or injuries. Each cross-referenced to its source.

  5. 05

    Expert-attention flags.

    The points that deserve your attention, ranked by significance. Supporting evidence one click away. Recommended action attached. The expert decides what stays in the report.

    HIGHMEDIUMLOW

Notora Med does not do the following.

  • It does not write the report.
  • It does not give a causation opinion.
  • It does not opine on prognosis, condition, or quantum.
  • It does not autonomise the expert's role; it accelerates it.

Every claim must be source-cited. Where the AI cannot cite a source, it does not make the claim.

The expert remains the signatory. The expert remains in charge.