Your own Authorization Server. In addition to the platform Authorization Server, AI Gateway lets you validate access tokens against your own OpenID Provider. Just provide the provider's Well-Known URL on the General screen: the gateway discovers the issuer and the public keys, validates the configuration when you save, and starts accepting only tokens issued by it.
REST API selection when registering MCP Servers. When creating an MCP Server from a catalog API, the selector lists only REST APIs, which are the ones that have an OpenAPI contract for generating the tools. This keeps the list leaner and avoids selections that would not produce a valid MCP Server.
MCP as Proxy: exposure and governance of existing MCP Servers. In addition to turning APIs into MCP Servers, the AI Gateway can now also sit in front of MCP Servers that already exist — internal to your company or from third parties — acting as a single point of governance, authentication, and observability.
You register an existing MCP as an origin, choose which tools to expose to your agents (allowlist), define the authentication mode, and route all traffic through the AI Gateway control layer, without rewriting, migrating, or re-hosting anything.
Support for custom and self-hosted language models. The AI Gateway now goes beyond traditional LLM providers (OpenAI, Anthropic, Gemini, among others) and allows integration with local, custom, or self-hosted language models — ideal for cost optimization, performance, compliance, or data sovereignty scenarios. You can also combine local and traditional models with priority rules.
Passthrough authentication for MCP Servers. The AI Gateway's MCP Servers now support the Passthrough authentication mode. Previously, when calling the business API, the MCP Server always generated its own service token (client_credentials). With Passthrough, the token of the end user logged into the agent can be passed on to the API, enabling scenarios where the API needs to identify the user to apply its own access rules — without giving up gateway governance.
AWS Bedrock with Assume Role. The AWS Bedrock integration can be authenticated through the Assume Role mechanism, where credentials are resolved at the infrastructure level, without relying on a static key registered in the gateway. To use it, just leave the API Key field blank when configuring a Bedrock provider. Authentication with an API Key remains available.
Prompt Guard with moderation and regex combined. The moderation and regex checks can be applied together in the same Prompt Guard (Request) policy. This makes it possible, for example, to submit the prompt to the moderation model and, at the same time, block specific patterns via regular expression, with a single custom response for both cases.
AI Gateway integrated into the Sensedia Platform and the Multi-Gateway strategy. The AI Gateway is now officially part of the Sensedia Platform, available on the home page alongside the other products and with unified access management via Access Control.
It also now operates integrated with the Multi-Gateway strategy: you can consume APIs from the federated catalog and expose them as tools and resources via MCP Servers, regardless of the gateway or API Manager of origin. In practice, the AI Gateway can be applied on top of existing API ecosystems, extending Federated API Management coverage to the AI context.
New hybrid infrastructure model. The AI Gateway now operates with a clear separation of responsibilities between platform and execution. This model supports multi-cloud and distributed scenarios, ensuring flexibility with centralized governance.
Sensedia AI Gateway. To enable secure, governed, and scalable adoption of Artificial Intelligence, we launched the Sensedia AI Gateway.
You can now orchestrate AI agents and LLMs with centralized governance, advanced security, and full observability across your entire architecture.
We use cookies to enhance your experience on our site. By continuing to browse, you agree to our use of cookies.Learn more