Learn how to add and configure self-hosted or external AI models to TrueFoundry AI Gateway for centralized management and inference.
If you run LLMs on your own infrastructure — on-premises GPUs, private cloud instances, or any model server not deployed through TrueFoundry — you can connect them to the AI Gateway by providing the endpoint URL and authentication details.Once registered, these models appear in the gateway model catalog alongside cloud providers and benefit from all gateway features: routing, guardrails, rate limiting, cost tracking, and observability.
Your model server must expose an HTTP endpoint. The gateway works best with OpenAI-compatible APIs, which is the default output format for popular inference frameworks:
Follow these steps to add a self-hosted or external model (deployed on TrueFoundry or elsewhere) to the AI Gateway.
1
Navigate to Self Hosted Models in AI Gateway
From the TrueFoundry dashboard, navigate to AI Gateway > Models and select Self Hosted Models.
Add model to AI Gateway
2
Add Collaborators
Add collaborators to your account, this will give access to the account to other users/teams. Learn more about access control here.
Add collaborators for the model
3
Configure Model Details
Give a name to your hosted model and add ModelId, add the URL to the hosted model. Choose the correct Model Server for your model and optionally add Auth Data which will be used for Authentication of request to the model.