Inputs arrive
Email, forms, calls, meetings, files, deadlines, and system events create new work.
AI agents for
Client intake, matter knowledge, documents, deadlines, and billing compete for the same expensive attention.
Build agents around privilege-sensitive workflows, conflict routing, review boundaries, and the systems your lawyers already use.
The operating problem
The useful question is not whether AI can answer a question. It is whether an agent can move a controlled workflow from one verifiable state to the next.
Email, forms, calls, meetings, files, deadlines, and system events create new work.
People reconstruct the client, project, document, approval, and next action across multiple tools.
Missing provenance, silent assumptions, delayed review, and unclear ownership make automation hard to trust.
A configured role gathers the context, acts within limits, and routes exceptions with evidence.
Recommended roster
Each promise below is rewritten around the industry workflow. The detail page shows the reusable role architecture.
Intake Agent
I turn a new inquiry into a conflict-routed, review-ready intake file.
Open AnikaDocument Agent
I extract structured facts from case files and show the source for every value.
Open OrenMatter Agent
I keep the matter timeline, documents, owners, and blockers visible.
Open MartaDeadline Agent
I preserve the source and escalation chain behind every critical date.
Open DariaBilling Agent
I turn work evidence into review-ready time entries and pre-bills.
Open EllisDesign obligations
These are architecture requirements to resolve during discovery and design. They are not compliance guarantees.
Attorney-client privilege and access segregation
Conflict-review ownership
Source traceability for extracted facts
Human approval for legal and commercial decisions
Integration inventory
Integration names indicate common targets for discovery. Availability, permissions, API coverage, and usage rights are verified during scoping.
AI Readiness Audit
In one working session, we map the workflow, systems, approval boundaries, risks, and the most useful first deployment.