Data Governance
Set the governance strategy and operating model, assign clear ownership and stewardship for data domains, and create policy and standards teams can adopt consistently.
Build Trust Into Every Layer of Data and AI.
We help organizations turn governance from policy into an operating capability, connecting accountability, technology, controls, workflows, evidence, and continuous monitoring.
Trust must be operational
Governance fails when it exists only in documents or committees. Effective governance must show up in how data is created, transformed, accessed, shared, certified, used by AI, monitored, and changed. We design governance so roles, policies, technology, and evidence work together across the lifecycle.
Trust control plane
- Data governance
- AI governance
- Access governance
Data Management
Manage metadata and the business glossary, trace lineage from source to use, and govern catalogs, data quality, master and reference data, critical data elements, and data products.
AI Governance
Turn responsible AI principles into enforceable policy, register every AI use case through a consistent inventory and intake process, and classify each one by risk and impact.
AI Lifecycle Controls
Define checkpoints from data readiness to deployment, and govern how models, prompts, tools, and agents are evaluated, permissioned, versioned, and changed.
AI Risk & Monitoring
Assess the risk of third-party AI and vendor models, and monitor AI in operation for performance, safety, drift, incidents, and cost.
Privacy & Security
Data classification, privacy, retention, identity and access controls, encryption, security architecture, threat protection, and policy alignment.
Certification & Assurance
Certify data products, analytical assets, and AI capabilities against defined readiness criteria, retain the evidence, set recertification triggers, and measure governance effectiveness.
Governance Technology
Configure catalogs, workflows, business glossaries, metadata models, lineage, stewardship experiences, DQ integrations, and governance automation.
Governance designed for scale
Our goal is to reduce ambiguity without creating unnecessary bureaucracy. We define where decisions belong, which controls are required, what evidence must be retained, where automation is possible, and how exceptions should be managed. The operating model is designed to scale with business domains, data products, platforms, and AI adoption.
Make trust measurable and governance executable.
We can help you establish or modernize the governance operating model, controls, technology, and accountability required for trusted Data and AI.