Kong AI Gateway sits at the connectivity layer of your agentic architecture — between your agents and everything they're trying to reach.
Unified control over every context call. Whether an agent is calling another agent, a database, a large language model (LLM), or a third-party API, every call passes through Kong. That means one place to set policies, one place to observe behavior, one place to debug.
Rate limiting and circuit breakers. When an upstream tool is struggling, Kong handles the fallback — not the agent. Retry logic, timeout enforcement, and circuit breaker patterns protect your workflows from cascading failures.
Semantic caching. Context retrievals that produce the same result don't need to hit the source twice. Kong caches semantically similar requests, so your agents get fast answers and your external systems don't get hammered.
Authentication and authorization. Every agent-to-tool and agent-to-agent call can require authentication, with fine-grained authorization policies enforced at the gateway. An agent that should only read from a CRM can't write to it — regardless of what the model decides to do.
Full observability. Structured logs of every retrieval and mutation, with latency, status, and payload metadata. When a workflow goes wrong, you know exactly what context each agent had and what it did with it.
LLM-agnostic routing. Route context retrieval calls across multiple LLM providers with fallback, load balancing, and cost controls. Your agents aren't locked to one model.