Short answer: An API gateway manages API traffic, while AI agent governance controls which tools and business actions an agent may use, under which policy, before the request reaches the API.
Traffic controls and agent intent are different layers
An API gateway is designed to authenticate callers, route requests, validate traffic, and apply limits at an API boundary. Those controls remain important for APIs used by people, services, and agents.
An agent governance layer understands the named tool, agent role, user context, policy assignment, approval state, and model-facing response rules. It can block an unsafe business action before a downstream credential is used.
How the layers divide responsibility
- Agent governance identifies intent. It evaluates the agent, named action, business parameters, and assigned policy.
- Agent governance resolves credentials. It retrieves a downstream credential without handing it to the agent.
- The gateway receives governed traffic. It applies API authentication, routing, quotas, threat protection, and protocol validation.
- The API performs its business logic. Existing service authorization and data rules still apply.
- Agent governance filters the result. It can remove data that should not enter the model context.
- Both layers produce evidence. Agent audit events and gateway traffic logs provide complementary views.
How KeyRunner complements an API gateway
KeyRunner sits at the agent execution layer and can work with APIs already managed through Kong, Apigee, MuleSoft, AWS API Gateway, or other gateway products. It does not require teams to remove their existing API controls.
KeyRunner adds policy-curated tool discovery, per-agent and per-action authorization, runtime credential isolation, approval gates, response redaction, and agent-aware audit logs before and after the gateway-managed request.
Enterprise checklist
- Keep gateway authentication and traffic controls
- Add agent and tool identity
- Check business policy before execution
- Keep credentials outside model context
- Add approval for high-impact actions
- Link agent and gateway audit identifiers
Frequently asked questions
What is the difference between an API gateway and AI agent governance?
An API gateway manages API traffic, while AI agent governance controls which tools and business actions an agent may use, under which policy, before the request reaches the API.
Can an API gateway identify an AI agent?
A gateway may authenticate a workload identity, but it usually does not contain the complete agent role, tool policy, approval state, or model response rules needed for agent governance.
Does KeyRunner replace an API gateway?
No. KeyRunner governs agent execution and complements the routing, traffic, and API protection controls provided by a gateway.
Related KeyRunner guides
- How Do AI Agents Access APIs Without Exposing Credentials?
- What Is MCP Security and How Do You Govern MCP Tools?
- How Do You Enforce Least Privilege for AI Agents?
- Agentic Security and AI Governance Guide
Explore the KeyRunner secure agent runtime, step through the live governance scenarios, or talk with the KeyRunner team.