Omar AI

Service 02

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.

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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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Support Inbox & Voice Agents

Proposal from a discovery call

Interactive demo

A first-draft proposal, built from the call and your own approved material, waiting for a person to approve it.

Sample data, invented for this demo. No account needed, no personal data collected, and no real message, email or CRM record is created.

  1. Harbourline Freight
  2. Read the brief
  3. Extract requirements
  4. Select approved material
  5. Draft the proposal
  6. Approve and save to CRM
Sample input
RAY (Harbourline): …so the bottleneck is the quote desk. Three people, and
every quote starts from a blank page even though ninety per cent of what goes
in it is the same.

YOU: How many quotes a week?

RAY: Forty, maybe fifty in peak. Each one is forty minutes of someone pulling
rates out of the TMS and retyping them. Then it sits waiting for Priya to sign
it off because she's the only one who checks the fuel surcharge.

YOU: And if the surcharge is wrong?

RAY: We eat it. Happened twice last quarter. That's the bit that actually
costs us.

YOU: What's the deadline?

RAY: We want it before peak season. That's the first week of March. Budget is
somewhere in the thirty to forty range, and I have to take it to Deborah.

Pick a sample and run the workflow to see what the system extracts.

Walkthroughs

Watch this one run.

The same workflow as a walkthrough. Written out in full underneath, so you can read it instead.

2 min

Proposal from a discovery call

Recording in progress — read the walkthrough below

Proposal from a discovery call

A first draft exists before the call notes go cold, and a person approves it.

  1. 1.A proposal request arrives, as a call recording or a written brief.
  2. 2.The system extracts the requirements: the problem, the volume, the constraint and the deadline.
  3. 3.It selects from material you have already approved, rather than writing new claims.
  4. 4.A first draft is assembled in your format.
  5. 5.A team member reads it, changes what is wrong, and approves it.
  6. 6.The CRM is updated and the follow-up is scheduled. The client is sent nothing until a person sends it.
Book a workflow assessmentTry the interactive version

Losing hours to work an AI system could handle?

Tell me about the process. I'll tell you straight whether it's worth automating — no pitch, no obligation.

Book a free audit call