Rencore
AI Agent Governance
Discover, inventory, and govern AI agents across Microsoft Copilot, Copilot Studio, and 15+ third-party AI platforms. One governance pane for every AI tool in use, from enterprise deployments to shadow AI adoption.
AI agent governance is the continuous discovery, inventory, risk assessment, and lifecycle management of AI tools and agents deployed across the enterprise. Microsoft 365 Copilot, Copilot Studio bots, Power Platform AI flows, plus Claude, OpenAI, Gemini, GitHub Copilot, and other third-party AI platforms, each with its own data access patterns, cost model, and risk profile. Rencore provides connectors to 15+ AI platforms, applying one governance framework across all of them.
The multi-vendor AI reality
Enterprises do not adopt AI from one vendor. Microsoft 365 Copilot handles productivity. Engineering teams use Cursor, Windsurf, and GitHub Copilot. Data teams use Claude and OpenAI APIs. Marketing uses Gemini. Specialized teams use Glean, LangDock, or Haystack for domain-specific tasks. Each tool has its own admin console, its own pricing model, its own data access patterns.
Without a unifying governance layer, the organization runs separate AI governance projects per vendor, each with different fidelity, different coverage, and different blind spots. The CISO cannot produce a consolidated AI risk view. Finance cannot attribute AI costs across departments. Compliance cannot demonstrate AI oversight for regulators.
Shadow AI compounds the problem
Not every AI tool adoption goes through procurement. A developer installs Cursor. An analyst signs up for Claude. A consultant uses ChatGPT with corporate data. These shadow AI adoptions process corporate data through external AI platforms without IT visibility, governance policies, or cost controls.
Shadow AI is the new shadow IT, but faster-moving, harder to detect, and with direct data exposure implications. Rencore’s connectors detect AI tool usage across 15+ platforms, making shadow AI visible and governable.
One governance framework for all AI
Inside Rencore, governance looks the same regardless of the AI vendor. Inventories use the same data model. Policies use the same severity scale. Reports use the same templates. Audit trails feed the same evidence pack. The CISO sees one AI risk dashboard, not 15 vendor-specific views.
This consistency matters for regulatory compliance. The EU AI Act requires organizations to maintain AI inventories and demonstrate oversight. Producing that evidence from 15 separate vendor consoles is impractical. Producing it from one governance platform is straightforward.
How to start
Connect your AI platforms to Rencore, starting with Microsoft 365 Copilot and Copilot Studio, then expanding to the third-party tools your organization uses. Within hours you will have a consolidated AI inventory: which tools, which users, what data access, what cost. That inventory is the foundation for AI governance policies, cost controls, and the regulatory evidence EU AI Act requires.
"We govern Microsoft 365. But half our developers use Cursor and Claude. Our data scientists use OpenAI. We have no visibility into any of it."
"The board wants an AI inventory for EU AI Act readiness. I cannot produce one because we do not know which AI tools are in use across the company."
What Rencore does
Discover
- Automatic AI agent and tool inventory
- Shadow AI detection across 15+ platforms
- Data access pattern mapping per AI tool
- User and department attribution
Govern
- Pre-built policies for AI usage
- Cost threshold alerts per vendor
- EU AI Act compliance policies
- Usage anomaly detection
Report
- Per-vendor cost dashboards
- AI inventory for regulatory evidence
- Usage and adoption reports
- Unified audit trail across all AI vendors
Frequently asked questions
How does Rencore govern AI agents beyond Microsoft Copilot?
What is Copilot governance?
Does Rencore support governance for AI tools beyond Microsoft Copilot?
What does the EU AI Act require for AI governance?
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