Service 03

Document & Intake Automation

The long, detail-heavy documents your team assembles by hand — intake packets, demand letters, summaries — built from the source records into an attorney-ready first draft.

Who this is for

Practices where the same document gets rebuilt from scratch on every case, and where the facts are scattered across notes, records, and billing.

PythonDocument AIGPT-4oClaudeRAGPostgreSQL
IntakeRecordsBilling
document
The problem
  • Assembling a document means reading everything first, and the reading is the expensive part.

  • Facts get transcribed by hand between systems, which is exactly where errors enter.

  • Because it is slow, it gets deprioritised — and the delay costs more than the drafting ever did.

How it's built

Five stages, and a human at the end.

Each stage is something you can watch run. Nothing here is a black box you're asked to take on faith.

  1. Ingest

    Intake notes, medical records, billing, and correspondence are read in, whatever shape they arrive in.

  2. Extract

    The facts that matter — dates, parties, treatments, amounts — are pulled into a structured record that can be checked at a glance rather than hunted for in prose.

  3. Assemble

    The structured record is composed into your firm's document format, in your ordering, with your standard sections and language.

  4. Flag

    Gaps, contradictions, and low-confidence extractions are surfaced explicitly rather than smoothed over, so review time goes where it's needed.

  5. Review

    An attorney starts from a complete draft with the underlying facts linked, and the work shifts from assembling to judging.

What you get
  • A document pipeline that runs on your real case files
  • A structured extraction schema matched to your practice
  • Output in your firm's own template and voice
  • Confidence flags and gap reporting on every draft
  • Human review built into the path, not bolted on
  • Tuning as your format evolves
Proof

AI Demand-Letter Generation for a Personal-Injury Firm

Read the case study
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