AI Agent Governance and Security Product for Enterprise Agents
For teams evaluating an AI agent security product or AI agent governance product, Rutile gives security and platform teams a control plane for agent inventory, delegated authority, JIT/JEA access, MCP/A2A proxy enforcement, runtime monitoring, and audit-ready evidence.
Core product modules
Each module maps to a concrete governance task required before agents can safely operate in production, making Rutile practical for AI agent security product and AI agent governance product evaluations.
Agent Discovery & Registry
Discover active agents and MCP servers, assign owners, record purpose, connected tools, risk tier, lifecycle dates, and allowed data scopes.
Agent Identity & Delegation
Bind agent actions to a human owner, business purpose, model, runtime, and downstream delegation chain.
JIT/JEA Permission Broker
Issue time-bound, task-bound, and data-bound access instead of long-lived API keys or broad standing privileges.
LLM/MCP/A2A/Tool Proxy
Enforce policy before tool calls reach SaaS, APIs, databases, files, cloud resources, or agent-to-agent workflows.
Runtime Monitoring & Kill Switch
Detect policy drift, suspicious tool use, data exfiltration patterns, and excessive autonomy, then deny, revoke, quarantine, or terminate.
Audit, Compliance & Reporting
Generate evidence across requester, agent, model, prompt hash, tool, resource, permission, policy decision, risk score, and outcome.
Agent Discovery & Registry
Select a module to see where it sits in the runtime path.
Registry signal
Discover active agents and MCP servers, assign owners, record purpose, connected tools, risk tier, lifecycle dates, and allowed data scopes.
Runtime enforcement flow
Rutile sits between agents and the systems they operate. It does not stop AI adoption; it gives teams a trusted execution path.
1. Register
Agent metadata, owner, allowed tools, risk tier, and expiration are registered before production use.
2. Evaluate
Every LLM, MCP, A2A, SaaS, or API call is evaluated against identity, context, policy, and data scope.
3. Grant
If allowed, Rutile brokers JIT/JEA access and records the permission boundary.
4. Monitor
Runtime signals, tool results, and policy decisions are streamed into audit and security workflows.
Rutile compared with adjacent controls
| Control | Primary target | Gap | Rutile role |
|---|---|---|---|
| LLM Firewall | Prompt risk | Focused on text risk at the model boundary. | Controls identity, authority, tools, access, runtime, and evidence. |
| Network Proxy | Traffic | Does not understand agent ownership or delegation intent. | Evaluates AI-native context before tool execution. |
| Single-vendor agent admin | One platform | Limited to the vendor ecosystem. | Designed as an independent control plane across agent stacks. |
Buyer value
Rutile converts agentic AI from an exception-driven security review into a repeatable operating model.
For CISOs
Approve agent deployment with ownership, least privilege, runtime controls, and audit evidence.
For IAM teams
Extend identity governance to non-human AI agents without replacing the existing IAM stack.
For platform teams
Ship agentic workflows faster because security controls are built into the execution path.
Product FAQ
What is the recommended PoC scope?+
Start with agent registry, policy proxy, JIT tool access, and audit logs. This proves inventory, enforcement, permission boundaries, and traceability.
Can Rutile support private deployments?+
Rutile can be evaluated for SaaS, private cloud, and on-prem or hybrid deployment patterns based on customer requirements.
Runtime enforcement flow
Rutile sits between agents and the systems they operate. It does not stop AI adoption; it gives teams a trusted execution path.