Service pillar

Data Governance

Lineage, provenance, consent and quality — the substrate every AI control eventually leans on.

Make your data estate legible to AI and privacy regimes in the same artefact. Lineage, training-data provenance, retrieval manifests, consent and purpose ledgers — indexed to the obligations that actually bind the work.

Outcomes we deliver

Each outcome is a signed, dated artifact your regulator, your auditor and your board can read — and that your practitioners can keep working with long after we walk away.

End-to-end lineage for training, fine-tuning and retrieval corpora
Consent and purpose ledgers aligned to PIPEDA, Law 25, GDPR
Data-quality controls indexed to model risk and NIST AI RMF Measure
RAG and vector-store manifests a regulator can read

Compliance agents in this pillar

Each agent is bounded, instrumented and auditable. Our specialists direct, review and sign off; the agents do the mechanical work at a multiple of the pace of traditional firms.

Lineage Agent

Builds end-to-end lineage for training, fine-tuning and retrieval corpora — sources, transformations, consent basis, downstream models and decisions.

Consent Ledger Agent

Maintains consent and purpose ledgers aligned to PIPEDA, Quebec Law 25 and GDPR — with ADM disclosure text, withdrawal handling and purpose-limitation records.

RAG Manifest Agent

Produces retrieval-augmented generation manifests a regulator can read — corpus provenance, index governance, grounding evaluation, change log.

Data-Quality Agent

Operates data-quality controls mapped to model risk and NIST AI RMF Measure functions — completeness, accuracy, drift, representativeness.

Recommended playbooks

Each playbook walks from first discovery through artifact. Phases, controls, evidence. Agents assist the mechanical steps; specialists own the sign-off.

EU AI Act · Assessment

EU AI Act High-Risk System Playbook

Classify use cases against Annex III, build the Article 9 risk management system, and compile the Annex IV technical file your conformity assessment will depend on.

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ISO/IEC 42001 · Controls

ISO/IEC 42001 AIMS Stand-Up Playbook

Build a certifiable AI Management System: scope, policy, objectives, risk, controls, audit. Mapped to your portfolio.

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Quebec Law 25 · Privacy

Quebec Law 25 PIA Playbook

Privacy Impact Assessments, ADM disclosures, cross-border transfer assessments — produced against the clause and the regulator guidance.

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Cross-framework · Controls

Agentic AI Governance Playbook

Multi-step autonomous agents, tool-calling chains, and the oversight these systems demand. Agent cards, action budgets, kill switches.

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Cross-framework · Documentation

RAG Assurance Playbook

Retrieval-augmented generation has its own attack surface — source provenance, index drift, poisoning risk. Control it.

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Cross-framework · Vendor

Foundation Model Due Diligence Playbook

Bringing a GPAI, Claude, GPT, Gemini, Llama or sovereign model into scope — the diligence a regulated deployer is now expected to perform.

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Cross-framework · Monitoring

Continuous Control Monitoring Playbook

Drift, performance, outcome and complaint monitoring in one pipeline — outputs a supervisor can act on.

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DORA · Controls

DORA for AI Systems Playbook

ICT risk management and incident reporting where AI is in the critical path — for EU-facing financial entities.

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Stand up data governance on an artifact your regulator will read.

Tell us where your portfolio sits today. We will map the frameworks, deploy the compliance agents, and put our specialists beside your second line.