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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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20 Modules
CLI-01
Client Disclosure and Consent Guidelines
Client disclosure and informed consent framework for transparent AI use in legal engagements
Module
1–2 hours per new matter; 30 minutes per material AI change
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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-03
Vendor Data Protection Obligations
Canonical checklist for reviewing and negotiating AI vendor data protection agreements.
Module
3–6 hours per vendor engagement, depending on complexity and negotiation cycles
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GOV-01
Defensible AI Governance Framework
Establish the governance structure, policy suite, and risk register that make Legal AI defensible to boards and regulators.
Module
2–4 weeks first run; 1 day annual review
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GOV-02
AI Use Policy
Define what AI use is permitted, prohibited, and supervised across the legal department — the operational policy that makes AI governance real.
Module
Initial deployment 2–4 weeks; 1 day for annual review
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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-04
Bias Testing & Monitoring Methodology
Pre-deployment bias test and continuous fairness monitoring checklist for legal AI systems
Module
Pre-deployment testing: 2–4 weeks per AI system; continuous monitoring: ongoing; quarterly audit: 1–2 days
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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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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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