One agent.
A customer support bot built on LangChain. Governing it takes 8 layers: identity, access control, data siloing, oversight, observability, context management, hierarchy, and interoperability.
Manageable for one.
Now imagine thousands.
50,000 developers at a Fortune 500 bank build agents on LangGraph and open source — bypassing the centralized platform. An HR agent trains on all employee data with no access controls.
We find 2–3x more AI assets than security teams know about.
The invisible ones.
43% of agents are unknown to security teams. Shadow AI services proliferate. Test agents stay in production. Third-party tools embed agents nobody approved.
43% invisible. Zero oversight.
Where this is going.
Agents deploy agents. MCP. A2A. Multi-agent orchestration. Trust becomes transitive. Delegation chains nobody can audit.
Nobody governs this.
Guard0 sees everything.
The AI Asset Graph maps relationships, not inventories. Every agent, every permission, every data flow — organized, color-coded, queryable.
Graph, not list.
Accountability, end to end.
Discovery finds what exists. Governance maps what it can reach. Enforcement stops what shouldn’t happen. When every agent is visible and every action is auditable — trust isn’t something you declare.
It’s something you prove.
When every agent is visible, every action is auditable, and every drift triggers a response — trust isn't something you declare. It's something you prove.
Compliance maps itself. Governance becomes automatic. And trust? Trust is what happens when accountability actually works.
The average enterprise finds 43 shadow agents
in their first scan. What will you find?
Agentless. Read-only by default. SaaS, Private SaaS, or On-Prem.