Charlie Fuller · Legal AI Architect · privacy & AI governance

Legal AI a firm can actually deploy.

The models can draft and the systems can hold the law. I build the layer that makes it safe to turn on inside a firm, and every diagram here is a system I’ve designed or shipped.

I’m the rails. The brain and the library are solved. I build the governance layer that makes AI deployable.
The boundary holds. The platform recommends, a licensed attorney decides. No fabricated cases, no invented citations.
Provable, not asserted. Client data isolated at the foundation, every decision logged and reproducible.
Shipped, not slideware. NDA triage, severance across three countries, contract review at 360/hour, cite verification.
ABA Model Rules 1.1 · 1.6 · 5.3 · 5.5 ABA Op. 512 GDPR EU AI Act NIST AI RMF CCPA / CPRA

Every authority cited on these pages is verified good law.

Start here: Legal AI OS → Read the full overview → How I build: my process →
The specialization
Privacy & AI governance
How the AI handles data, assessed before it ships.Open →
The boundary
Where the AI stops and the lawyer starts, drawn, not assumed.Open →
Governance model
The pillars that make firm-wide AI deployable.Open →
Shipped
Full platformWhole firm, end to end
The same governance everywhere, not per tool.Open →
NDA triageSeconds, not days
Field NDAs approved or routed, with proof of every call.Open →
Separation & severance2–4 hours → 30 seconds
Across three countries, under one governance model.Open →
Privacy researchHalf the work automated
Vendor privacy paperwork researched and pre-drafted.Open →
Full project registryAll of it, indexed
Every standalone legal project and client engagement, in one place.Open →
Legal metricsAsk in plain English
Outside-counsel spend and legal-ops data, queried directly.Open →
State filingsDeadlines, met
Secretary of State filings automated across registered states.Open →
Cowork pluginIn the workspace
Policy answers in context, behind access controls.Open →
MCP serverThree tools, one protocol
Deterministic legal tools served over Streamable HTTP.Open →
Matter intake evaluatorThe proof-of-concept
Standalone intake POC that proved the pattern before Legal-OS absorbed it.GitHub →
Contract review360 contracts / hour
Five specialized agents, RAG-powered, governance under the hood.Open →
Under the hood
Citation verification
Every authority checked: real, correctly cited, still good law.Open →
Cite check, case study
Three authorities. Two with conditions. One not a real case.Open →
Isolation
Client data that never leaves the firm’s control.Open →
Storage, in flow
How each storage architecture moves data, step by step.Open →
NLP preprocessing
Deterministic segmentation that fixes naive period-splitting.Open →
Matter intake pipeline
Router classifies, evaluator scores, audit captures.Open →
Evaluation, without an answer key
Programmatic checks, independent scorers, a hard veto.Open →
RAG that survives a firm
Ethical walls applied after retrieval; version ambiguity handled.Open →
Frameworks & market
The maturity model
Six dimensions × four stages for where a firm is and where it’s headed.Open →
Maturity, applied
The model estimated against Ashurst Perkins Coie.Open →
Agentic org → legal
McKinsey’s agentic-organization research, translated to law firms.Open →
Fault-Line Radar
Fault-Line Radar
A prediction engine for legal AI. Start here and pick your way in: how it works, the scoring engine, the screen, the sources, or how I built it.Open →
Client engagement — APC
Legal OS — APC
Five-layer OS for the post-merger firm.Open →
APC ↔ Harvey ↔ Legal OS
How the engagement maps across platforms.Open →
Four mandates
Builder, tracker, teacher, protector, mapped to work.Open →
JD alignment
Every JD requirement mapped to projects and deltas.Open →
ABA 512 → controls
Six duties mapped to engineered controls.Open →
Evaluation lifecycle
15 methods across 6 stages, hard veto rule.Open →
Discovery narrative
12-week engagement timeline, from AI to impact.Open →
ROI framework
3 metrics → dashboard → AFA pricing → reporting.Open →
The economics
The AI Profit ParadoxInteractive · print to PDF
Why hourly billing turns AI into a loss and fixed fee into profit.Open →
The Seam FinderInteractive · print to PDF
Where AI stops and the lawyer starts. An honest band, not a fake decimal.Open →
AI hits a law firmTwo tracks, one firm
What AI does to the billable hour, the redline, the pyramid.Open →
Law-firm simA digital twin
Monte Carlo and Bayesian search over your firm’s levers.Open →
How the sim worksUnder the hood
The engine in plain English, then the mechanism.Open →
Let’s talk legal engineering. Open to privacy and AI-governance roles inside legal teams.   Connect on LinkedIn · github.com/motorthings · All diagrams
© 2025–2026 Charlie Fuller