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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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38 Modules
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-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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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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STR-02
AI Strategy Canvas
Facilitated canvas to define legal’s AI vision, ambition, ROAI targets, and augmentation roadmap.
Module
4–8 hour facilitated workshop plus 2-week stakeholder sign-off cycle
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STR-03
Risk Matrix — Use Case × Risk Taxonomy 2026 × Likelihood
Systematic risk-scoring framework for AI legal use cases aligned to Risk Taxonomy 2026.
Methodology
3–6 hours per use case; 2–3 days for full portfolio review
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STR-07
AI Task Force Charter
Stand up the AI governance body that owns strategy, AI BoM oversight, and DPS production for the legal department.
Module
Initial setup 90 days; ongoing 2–4 hours/month per core member plus quarterly reviews.
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SUS-01
Vendor Performance Review Cycle
Evaluate AI vendor performance quarterly across five weighted dimensions with Risk Taxonomy 2026 mapping and Agentic Tier governance checks.
Module
3–4 hours per vendor per quarter once established
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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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