Client intake
Email thread, documents, deadlines, matter type.
Targeted AI workflow
Prepare a legal intake brief with a strict review gate.
Workflow map
For sensitive work, the automation must be boring in the best way: permissions, audit trail, and a mandatory human gate.
Client documents, legal research, and case-management tools feed a controlled brief. The lawyer reviews before any answer or deadline is created.
For sensitive work, the automation must be boring in the best way: permissions, audit trail, and a mandatory human gate.
What the automation connects
Client documents, legal research, and case-management tools feed a controlled brief. The lawyer reviews before any answer or deadline is created.
Email thread, documents, deadlines, matter type.
Contracts, IDs, evidence, prior exchanges.
Internal memos, doctrine, jurisdiction notes.
Facts, missing pieces, risk flags, draft questions.
Validate legal framing, wording, and next step.
Reply, task, deadline, document checklist.
Security controls
A law-firm AI workflow should redact or pseudonymize confidential client data before any model call, then use API data controls, audit logs, and lawyer approval to reduce data breach and professional secrecy risk.
Client names, addresses, matter references, evidence identifiers, privileged strategy, and other sensitive data are replaced with stable placeholders before the LLM receives context.
Use paid API configurations with clear data-processing terms, retention controls, and no model-training use by default; request zero data retention where the endpoint and provider plan support it.
The lawyer validates legal framing, re-identification, deadlines, and client-facing wording before the workflow updates the matter or sends any communication.
Why this workflow works
For sensitive work, the automation must be boring in the best way: permissions, audit trail, and a mandatory human gate.
NEW PROJECT / OPEN CHANNEL
Describe the workflow, the friction, and what a useful outcome would look like. We will start there.