Trusted by consumer brands
WHAT IS CHANGING IN AI & DATA GOVERNANCE?
Organizations have AI use cases running in production.
Governance teams focus their controls on the data layer, highlighting the need to extend oversight to AI models and applications.
of organizations have implemented governance tools for AI agents.
Sources: 1, 2 & 3.BARC, The State of Data and AI Governance, 2026
Use cases
Profile priority data sources, identify quality issues and define rules, thresholds and scorecards to help teams establish trusted data for analytics and AI.
Data Quality & ObservabilityFoundation Studio
Improve catalog coverage, establish approved business definitions and trace data to its source so teams and AI applications can use data with greater confidence.
Data Governance Operating Model
Address recurring customer and product data issues through master data management, helping stewards improve consistency across business records.
Master Data Management
Classify sensitive data, establish access and classification policies, and identify where additional controls are needed before data is exposed to RAG pipelines or AI agents.
Compliance Gap Assessment
Establish risk-based approval gates, evaluation standards and human oversight across the AI lifecycle. Document models and agents, monitor AI performance, and maintain audit trails to make AI decisions and actions traceable.
Agentic AI Readiness AssessmentAgentic AI Governance
The path
The data foundation for AI & data governance
We bring together data governance and AI controls to help organisations build trusted data, manage risk and enable responsible AI at scale.
Studio AppsPulse apps & Prism
AI TransformationAI Services
Foundation Studio
3x fasterto measured pilot results
MDM Studio
4 core capabilitiespre-built for mastering and managing trusted records
GRC Pulse
100% traceabilityContinuous control assurance
Standardizing product data to scale catalog operations
Improving Data Governance and SLA Visibility for a Global BPO Leader
We stay after go-live: every decision gets an insight, an owner, an action and an outcome.
Governance aligned with business decisions and risks.
Runs in your tenant with approved models and sandboxed testing.
Works with Unity Catalog, Microsoft Purview and Snowflake Horizon.
Policies, certified glossary, quality rules and adoption tracking.


Partner


FAQ
Establish clear data ownership, quality rules, and consistent definitions to create trusted, decision-ready data.
Build a governed data foundation with reliable data, clear lineage, and defined access controls to support AI initiatives.
Apply risk-based approvals, human oversight, model evaluation, and audit trails across the AI lifecycle.
Define policies, assign ownership, and maintain traceable evidence of controls, decisions, and remediation actions.
Bring one challenge, and we’ll show you what needs to change.