Audit First
Start with readiness. Build the platform second.
The current public offer is an ABA 512 and operating-model review for firms already using AI. The broader platform story is the downstream implementation direction, not a claim that finished software exists for every surface today.
First Paid Engagement
A workflow review for firms that already know AI is in the building.
Current AI usage map
Identify where AI is already touching intake, drafting, research, communication, or billing instead of debating hypotheticals.
Risk and supervision review
Review confidentiality boundaries, human approvals, client-facing disclosures, and where current habits are too informal to defend.
Workflow priority list
Choose one surface to fix first so the firm does not try to govern every AI workflow at once.
Implementation direction
Translate the review into a sequence for platform work, playbooks, or policy changes instead of a generic roadmap slide.
Build Direction
If the review turns into implementation work, these are the surfaces that usually come next.
The platform direction is still real. It is just downstream of the audit, not the thing the site should pretend is already solved.
AI Intake
Structured intake with explicit review, disclosure boundaries, and cleaner routing into the rest of the workflow.
- Lead triage
- Matter opening rules
- Document collection handoff
Matter Memory
A durable context layer for facts, decisions, documents, dates, and client preferences once the governance basics are in place.
- Timeline memory
- Source tracking
- Cross-matter search
Document Workflows
Drafting and review loops that preserve attorney accountability instead of hiding it behind model output.
- Draft review states
- Citation checks
- Firm-standard guardrails
Client Communication
Plain-language updates and response patterns that keep attorney review visible before anything reaches a client.
- Status updates
- Summary review
- Escalation rules
Pricing Operations
Billing and scope discipline that keeps AI-assisted efficiency commercially coherent and ethically legible.
- Scope logic
- Flat-fee discipline
- Internal profitability review
AI Governance
Policies, approvals, permissions, and audit visibility designed into the workflow itself rather than added as afterthoughts.
- Vendor controls
- Approval logs
- Policy references
Start with the self-audit, then decide whether the workflow needs deeper help.
The honest order is simple: score the current posture first, then use the waitlist for a deeper operating-model review if the fit is right.