AI agent governance is the control of what autonomous agents are permitted to do once they act on a person's behalf: which systems they reach, what authority they carry, and what record survives the session. Smartflow issues each agent a cryptographic identity and enforces its scope inline, across both MCP and A2A traffic.
AI Agents Are Acting on Behalf of Your Employees. Who Authorized Them?
AI agents are initiating payments, accessing customer records, executing trades, and connecting to enterprise systems through MCP and A2A protocols. Smartflow provides the governance layer that ensures every agent action is authorized, scoped, auditable, and revocable.
Key capability:
The Agentic AI Governance Gap
The March 2026 OpenClaw incident exposed what happens when AI agents connect to enterprise systems without governance. Over 21,000 exposed instances. OAuth tokens granting broad access. Agents moving laterally across Slack, Google Workspace, and internal APIs without triggering security alerts.
The problem is architectural. AI agents that can take actions in the real world require fundamentally different security controls than AI systems that only generate text. Traditional IAM was designed for humans clicking buttons. AIDA is designed for autonomous software acting on delegated authority.
How Smartflow Governs Agents
AIDA: Agent Identity and Delegated Authority
Every AI agent receives a cryptographic credential that specifies exactly what it can do. A ReadOnly agent cannot initiate a payment. A payment agent cannot exceed its transaction limit. An agent authorized for Account A cannot access Account B.
MCP Proxy Governance
Smartflow sits inline on MCP tool invocations. Every call from an agent to an external tool passes through Smartflow's policy engine. The gateway verifies the agent's AIDA credential, checks the tool against the authorized scope, enforces content policies, and logs the complete interaction.
A2A Protocol Governance
When agents communicate with other agents, Smartflow governs the inter-agent channel. It verifies that both agents have valid credentials and that the data exchanged complies with information barrier and DLP policies.
Related reading
Agentic AI · Agent authority scope · MCP security · Tool poisoning · Human-in-the-loop · AI incident response · Board reporting
Put this in the path of your own agents.
Policy enforced inline between your agents and every model and tool they reach, with a record bound to the human who owns it.
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