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The operational capability layer of the Legal AI OS.
Modules are the institutional artefacts a legal function runs to advance maturity, produce Defensibility evidence, and operate on canonical ground in front of a regulator or a board. Anchored across the 8 Pillars and 6 Operating Layers. Methodology-versioned. Editorially independent.
PILLAR
AUDIENCE
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29 Modules
ADM-01
Adoption Telemetry
Continuous measurement framework tracking AI training completion, adoption progress, AI BoM coverage, Class 6 governance incidents, and ROAI attribution across Protect, Comply, Grow, and Transform quadrants, producing DPS-grade evidence for the legal AI programme.
Telemetry source
Initial setup 4–8 weeks; continuous monitoring with weekly and monthly reporting cycles
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COT-01
Continuous Optimization Cycle
Systematically capture AI performance feedback, map signals to Risk Taxonomy 2026 classes, and execute ROAI-attributed optimization cycles across the legal department's AI portfolio.
Module
Initial setup 2–4 weeks; continuous telemetry; monthly analysis; quarterly planning and review (0.5–1 day per quarter).
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DAT-01
Data Governance Architecture
Establishes the foundational data governance policies for legal AI, covering classification, vendor data protection, Shadow AI governance, regulatory compliance, and Agentic Tier data provisions.
Module
3–6 weeks for initial framework; 1–2 weeks for annual review and updates
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DAT-02
Data Inventory & Classification Methodology
Classify every data asset by sensitivity level, assign AI processing permissions by classification, and build the governance record that proves Defensible AI adoption.
Module
Initial build 4–6 weeks; quarterly updates 1–2 days; annual review 3–5 days
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DAT-04
Data Minimization Methodology
Apply data minimization across every stage of the AI data lifecycle, govern shadow AI through the canonical Class 6 protocol, and build the evidence record that proves Defensible AI.
Module
Initial rollout 4–6 weeks; continuous monitoring with monthly and quarterly checkpoints
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DAT-05
Integration Architecture
Per-engagement blueprint for integrating legal department systems with AI tools through a three-tier architecture with canonical Agentic Tier API provisions, Class 6 Shadow AI detection controls, and Risk Taxonomy 2026 cross-walk.
Module
6–12 months for initial rollout; 1–2 weeks for annual review and major change assessments.
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GOV-03
AI Risk Register
Apply the Risk Taxonomy 2026 to identify, score, and mitigate AI risks across nine canonical classes — the register that makes your governance defensible.
Module
Initial setup 4–6 weeks; 2–4 hours per quarterly review cycle
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GOV-05
AI Incident Response Playbook
Detect, classify, escalate, and resolve AI incidents across all nine Risk Taxonomy 2026 classes — the playbook that closes the governance loop.
Module
Per incident; 15 minutes to activate; resolution timeline by severity; PIR within 30 days for Level 1–2
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GOV-13
Evidence Register Architecture
Per AI system × per Risk Taxonomy 2026 class: the contemporaneous proof the function holds — the operational substrate of Defensibility.
Module
4 hours first run per system; 1 hour quarterly refresh per system
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GOV-14
Delegation-Authority Register Architecture
Per Tier 3 and Tier 4 capability: the named record of what the system may decide, within what scope, with which human accountable.
Module
2 hours first run per Tier 3+ capability; 30 minutes quarterly refresh
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GOV-15
Governance Operating Cadence
Committee calendar mapped to AI Lifecycle stages — Concept intake through Sunset closure — with standing agenda, quorum, and gate evidence requirements.
Module
One-time setup 3 hours; standing committee meetings 60–90 minutes per cadence
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GOV-16
Materiality Calibration Methodology
Per Tier 3+ capability: which decisions require Full HITL, Exception-triggered HITL, or Audit-only — calibrated quarterly as performance and regulatory context evolve.
Module
3 hours first run per capability; 1 hour quarterly refresh
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Advisory
The full operating system in one Programme.
Programme Design and Strategic Retainer engagements operate the canonical Module sequence end-to-end — Defensibility evidence produced, Maturity progression evidenced quarterly, methodology version pinned. The Module Library is the artefact; the engagement is the operating posture.
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