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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.
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37 Modules
GOV-11
AI Incident Disclosure Standard
Governs the organisation's obligations and procedures for disclosing AI incidents to clients, regulators, and professional bodies.
Module
Disclosure decision: 4–8 hours per incident; regulator notification preparation: 1–3 business days; client disclosure drafting: 1 business day per affected client.
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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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INS-01
AI Liability & Insurance Posture
Assess professional liability exposure, insurance coverage gaps, and vendor indemnification adequacy for AI tools across the Risk Taxonomy 2026 nine-class framework.
Module
1–2 days initial per tool; 2–4 hours per tool at renewal or quarterly review
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MAT-01
Maturity Grid
The canonical Year-1 maturity instrument — plots organisational Adoption against AI Sophistication on a 5×4 grid to produce a defensible quarterly position and Maturity Stack-linked progression evidence.
Module
1–2 days for baseline; 0.5 day per quarterly review; 1 day annual strategic refresh
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MAT-02
Legal AI Readiness Baseline
The canonical 8-pillar readiness diagnostic that captures baseline maturity across all Legal AI OS transformation dimensions and maps current position to the MAT-01 2D maturity grid.
Module
1–2 days for full baseline; 0.5 day for quarterly review; 1 day for annual re-baseline
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MAT-03
Maturity Gap Analysis
Structured 6-step gap analysis to map current vs. target Legal AI maturity, risk exposure, and roadmap.
Module
2–4 days for baseline; 1 day for quarterly and annual refreshes
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MAT-04
Quarterly Maturity Review
Track AI transformation progress, ROAI realisation, and compliance status across all eight pillars every quarter.
Diagnostic input
4–6 hours per quarterly cycle once established
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MAT-05
Peer Benchmarking Methodology
Compare your organisation’s legal AI maturity, ROAI realisation, and risk class exposure against industry peers and top-quartile performers.
Diagnostic input
4–6 hours per quarterly cycle; 1 working day for annual review consolidation
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MAT-06
Board AI Reporting Architecture
Provides the structured report framework for presenting AI governance performance, risk posture, and maturity progression to the Board or Governing Partners.
Module
Report preparation: 2–4 days per quarterly cycle; 5–7 days for first report; 5–10 days for annual report.
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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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