Tools that manage, route, and protect API traffic between services and consumers. They were built to enforce rate limiting, authentication policies, and traffic visibility at the network edge.
API gateways solve a real problem: controlling who can call which APIs, at what volume, under what policies. They work well for network-layer enforcement: routing, rate limiting, TLS termination, and coarse-grained access control based on API keys or JWTs. Two gaps appear at the identity layer. First, API gateways verify that a request carries a valid token, but they cannot attest the identity of the workload that obtained that token. They see the credential, not the caller. Second, for AI agent traffic, gateways often cannot distinguish a legitimate task from a prompt injection or adversarial request, because they lack the workload context to understand the meaning of the interaction.
Aembit operates at the caller layer: it attests the runtime identity of the workload or AI agent before the request is made, and issues short-lived credentials bound to that identity. The two tools serve different sides of the API call. API gateways protect the provider (the API endpoint receiving traffic), while Aembit secures the caller (the workload making the request).
Aembit does not replace API gateways. Gateways handle network-layer traffic management that Aembit is not designed to perform.
Aembit integrates with API gateways such as Kong, AWS API Gateway, and Apigee by issuing short-lived, workload-bound JWTs or OAuth tokens that the gateway validates on inbound requests. This means the token arriving at the gateway is not a static API key or reusable secret. It is a short-lived credential tied to a specific, attested workload identity. Organizations already running a gateway can use Aembit to harden the authentication model for service-to-service and agent-to-service calls without replacing their existing gateway infrastructure.
API gateways and Aembit protect opposite ends of the same API call. A gateway is typically deployed inline on the data plane, sitting between the network and the API it protects: it handles routing, rate limiting, TLS termination, and coarse-grained access policy based on token presence. Aembit operates on the control plane, at the caller side: it attests the runtime identity of the workload making the request, enforces contextual access policy, and injects short-lived credentials without requiring the workload to store or retrieve them. For AI agent use cases, this distinction matters most. A gateway sees the request payload but has no context about whether the calling agent is authorized, healthy, or behaving as expected. Aembit establishes that trust before the call is made, so the token that arrives at the gateway already carries attested identity, not just a valid credential.
PAM handles human privileged sessions: an admin checking into a production server, a developer accessing a cloud console, a vendor connecting to a sensitive system. Ambit handles the other side: applications, services, Al agents, and CI/CD pipelines that need to authenticate to those same sensitive systems without human intervention. PAM is optimized for the relatively small number of human administrators in an environment – session-based, interactive, with approval workflows and session recording. A microservice or Al agent operating at scale makes thousands of authentication requests per hour, has no interactive session, and cannot wait for a human approval workflow.
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