TRUSTED DATA REFINERY
Governance Gaps for AI Agents
Close the governance gaps that prevent safe, controlled deployment of AI agents across your enterprise data using Trusted Data Refinery's metadata intelligence layer.
Closing the Gaps Microsoft's Native Tools Leave Behind
Metadata is the missing layer for enterprise AI. Enterprise AI, Copilot, and Agents cannot safely operate on raw unstructured data. They require context, permissions, meaning, and governance before content is used. Agents cannot act safely without trusted metadata that defines authority, sensitivity, relevance, and policy boundaries. Trusted Data Refinery provides this foundation.
The Agent Challenge
In the future of work, humans set intent, AI reasons, and agents act. But agents cannot act safely without trusted metadata that defines what they're allowed to do. Without governance, agents become sources of risk — accessing data they shouldn't, taking actions without authorization, and creating compliance exposure.
Trusted Data Refinery: Metadata as Control Plane
Metadata is what turns AI from "chatting" into "doing." Trusted Data Refinery transforms unstructured data in place into an enriched metadata intelligence layer:
Data Reader scans 8 million files per hour, extracting structural metadata across file systems and SharePoint.
Data Identifier normalizes and enriches metadata, identifying ownership, sensitivity, and relationships.
Smart Stack persists this intelligence as reusable Trusted Data Collections that agents can query safely.
Policy Boundaries for Agents
Smart Stack's policy-based organization ensures that agents only access data within their authorized scope. Sensitivity classification, ownership identification, and retention policies all contribute to the governance framework that controls agent behavior. Agents operate within boundaries defined by enriched metadata.
Model Context Protocol Integration
Trusted Data Refinery prepares data for Model Context Protocol (MCP) integration, enabling Copilot and agents to query and retrieve highly governed, compliance-safe Trusted Data Collections. The MCP Layer acts as the secure conduit between AI systems and the enriched metadata that Trusted Data Refinery produces.
Key Benefits
- Agent Safety: Metadata defines what agents can access and do.
- Policy Enforcement: Governance boundaries control agent scope.
- MCP Ready: Integration with Model Context Protocol for agentic AI.
- Audit Trails: Track agent actions for compliance and review.
Conclusion
The agentic AI future requires governance infrastructure that doesn't exist in raw data. Trusted Data Refinery provides the metadata control plane that makes agents safe and effective.
