Data & Governance for AI
Connect and govern the data your AI depends on: access control, policy, evaluation and the evidence to operate AI responsibly.
AI cannot compensate for fragmented, ungoverned data. And an enterprise cannot run AI it cannot control or measure. This practice covers both sides of that coin: making your data ready for AI, and putting policy, evaluation and evidence between AI and everything it touches.
What does AI-ready data actually mean?
Connected sources, resolved identities, governed access and current context, available where people and AI systems act. If your agents are grounded in stale or ungoverned data, everything downstream inherits the problem.
What we deliver
- AI data strategy: source connectivity, identity resolution, modeling and activation design.
- Identity-aware access controls for users, agents, tools and data sources.
- Data classification, redaction, retention and sensitive-content policy. Enforced, not just documented.
- Evaluation, audit trails, release gates and incident workflows, so quality stays visible as models and prompts change.
We align to established practice, including the NIST AI Risk Management Framework, as engineering rather than as a certificate. A successful pilot is not evidence of durable production quality. Measurement is.
Pairs with
AI practices that plug into this work
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The other crafts on the same foundation
Turn your data into AI-ready context
Every engagement starts with a conversation about the problem, not the tech.