Read
Gather context from the matter
The agent reads approved matter context, documents, notes, and task history so the draft starts from the real file, not a blank prompt.
Managed agent spoke
Legal document automation that prepares the work — without skipping review.
FirmOps uses supervised AI agents to read matter context, prepare document work, and route drafts or packets for approval. It is document automation built for law-firm control, not blind auto-send.
The workflow
Read, prepare, review — then approve.
The goal is not to remove judgment. It is to stop staff from rebuilding the same first draft or packet from scratch.
Prepare
Draft the packet or next document
It prepares the document, cover note, checklist, or follow-up packet with citations to the source context staff should review.
Review
Route for human approval
The result queues for staff or attorney review. Sends, filings, and record changes stay gated until a person approves them.
Good first use cases
Automate the preparation, not the professional judgment.
Legal document automation works best where the file already contains the facts, the output follows a known pattern, and a human can quickly approve or correct the result.
- Medical-record request packets and follow-up letters
- Client document checklists and missing-item requests
- Matter summaries for handoff, demand prep, or litigation review
- Draft status updates grounded in approved file context
Document examples
Start with documents that already follow a pattern.
The safest first wins are drafts and packets where the facts are already in the file and the final action still needs human approval.
Records packets
Prepare provider letters, request checklists, and follow-up notes from matter context.
Client missing-item requests
Draft a clear request for photos, bills, forms, or signatures without sending until staff approves.
Matter summaries
Create handoff summaries for demand prep, attorney review, or litigation transition.
Status updates
Draft client-facing updates grounded in approved file context and queued for human review.
Next step
Show us one document bottleneck.
The demo shows how a managed agent would read context, prepare the draft, and hold the action for review.