AI Agent Catalog & Governance
The catalog enterprise AI agents have always needed.
Register, discover, and govern every AI agent — with full visibility into its tools, MCP connections, prompts, permissions, and autonomous behaviors. All in one place.
Quick answer: An AI agent catalog is a centralized, continuously updated inventory of every autonomous AI agent an organization runs — including its tools, MCP connections, prompts, permissions, and risk tier. WiseRegent auto-discovers agents across your stack and gives every one an owner, an approval record, and an audit trail.
Agent-complete registry
More than a name and version. Capture the tools, MCP connections, prompts, permissions, and risk tier for every agent — automatically enriched from your stack.
Autonomous action governance
Define what agents can do, who must approve their deployment, and get a complete audit trail of every autonomous action taken on behalf of your users.
Works alongside MLflow
Your models stay in MLflow. WiseRegent adds the agent catalog layer on top — integrating with your existing model registry rather than replacing it.
Complete Agent Registry
Know exactly what every agent can do — and who approved it.
Most organizations can tell you which models they have. Almost none can tell you which agents are running, what tools they can call, what data they can access, or who approved their deployment. WiseRegent closes that gap with a structured registry for every agent artifact.
- Auto-register agents from LangChain, CrewAI, AutoGen, OpenAI Assistants, Bedrock Agents, and more.
- Capture every tool, MCP server, and API binding — including permissions and credential scopes.
- Version history for prompts, system configs, and capability changes across every deployment.
Agent Detail — customer-support-agent
Agent-Specific Governance
Govern autonomous behavior — not just model metadata.
Agents are fundamentally different from models. They act autonomously, chain tool calls, and can take irreversible actions. WiseRegent's governance engine understands agent semantics — so you can set policy for what agents can do, require human-in-the-loop approval for high-risk deployments, and maintain a tamper-proof audit trail of every action.
- Policy-as-code: define which tool categories require approval before an agent can call them.
- Human-in-the-loop gates: require explicit sign-off for agents with write access or PII scope.
- Immutable audit trail: every agent action, tool call, and configuration change is logged and signed.
Governance Policy — Agent Deployments
MLflow Integration
Your models in MLflow. Your agents in WiseRegent. Together.
MLflow is the standard for model registries — and WiseRegent has no intention of replacing it. Instead, WiseRegent connects directly to your MLflow and Unity Catalog instances, reading model metadata and linking it to the agents that depend on those models. You get a complete picture of your AI lineage without migrating a thing.
- Native MLflow connector: sync model versions, runs, and experiments in real time.
- Agent-to-model lineage: see which agents depend on which model versions — and surface blast radius when a model is updated.
- Unity Catalog sync: resolve feature tables and datasets referenced by agent tools.
Lineage — customer-support-agent
Register your first agent in under 5 minutes.
Connect
Authorize access to your agent framework, MLflow, and cloud accounts.
Discover
WiseRegent scans and surfaces every agent — including shadow agents nobody registered.
Enrich
Tools, prompts, permissions, and lineage auto-populated from your source systems.
Govern
Apply policy, require approvals, and generate audit-ready evidence packages.
Native integrations
Works with your agent framework and model registry
FAQ
AI agent catalog — frequently asked questions
What is an AI agent catalog?
An AI agent catalog is a centralized, continuously updated inventory of every autonomous AI agent an organization runs — including the tools it can call, its MCP connections, prompts, permissions, and risk tier. It answers "what AI agents exist, what can they do, and who approved them" in one place, instead of scattered spreadsheets and tribal knowledge.
How do I find shadow AI agents?
Connect your clouds and agent frameworks to WiseRegent's Unified Asset Catalog, which automatically scans for agent frameworks (LangChain, CrewAI, AutoGen, OpenAI Assistants, Bedrock Agents) and surfaces any agent running without a registered owner, approval, or risk classification — typically within minutes of connecting the first integration.
AI agent governance vs. model registry — what's the difference?
A model registry (like MLflow) tracks model versions, training runs, and metrics — it answers "what model is this?" AI agent governance goes further: it tracks what an agent can autonomously do — which tools it calls, what data it can access, what actions it can take on a user's behalf — and enforces policy and approval workflows around that behavior. WiseRegent integrates with your model registry rather than replacing it, and adds the agent governance layer on top.
Early access open
Govern your AI agents
before your auditors do.
Join the early-access programme. Shape the roadmap. Lock in founding rates. No credit card, no commitment.