Release Notes

Track new features, improvements, and fixes for each Sensedia AI Gateway release.

July 3, 2026

Azure AI Foundry as a new LLM provider. You can now register and route models exposed via Azure AI Foundry in the AI Gateway. Until now, the Azure integration was limited to Azure OpenAI (restricted to OpenAI models). With the new provider, you get access to the full model catalog available in Azure AI Foundry, all of them subject to the same AI Gateway policies, rate limits, and observability.

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.

Centralized scope management. The AI Gateway now handles access scopes in a dedicated module, with references in MCP Servers, LLM Routes, and AI Agents, and validation with the AI Gateway's embedded IDP. Scopes that used to be strings scattered across resources now have centralized registration and management.

AWS Bedrock as a new LLM provider. You can now register and configure language models running on AWS Bedrock directly from the AI Gateway administration panel. Agents can use models exposed on Bedrock as part of the inference flow, with the same capabilities as the other providers available in the AI Gateway.

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.