How can an AI gateway govern multiple AI providers?

Summary

• An AI gateway governs multiple providers by putting one control plane in front of every model, so teams reach OpenAI, Anthropic, Google, and other endpoints through a single governed interface instead of scattered per-provider credentials.
• It centralizes the four things that fragment across providers: authentication and API keys, access permissions, usage and cost tracking, and content policies.
• On Databricks, Unity Gateway registers each external provider as a Unity Catalog securable, so the same GRANT and REVOKE model that governs data also governs which users and agents can call which models.
• Requests, responses, token counts, and spend are logged to governed tables, giving one audit trail and one cost view across every provider.
• Because access runs through one OpenAI-compatible endpoint, you can add a provider, split traffic, or fail over to a backup model without rewriting applications.

How can an AI gateway govern multiple AI providers?

An AI gateway governs multiple providers by sitting between your applications and every model they call, turning a sprawl of direct connections into one governed path. Instead of each team wiring its own keys to OpenAI, Anthropic, Google, and internal models, every request flows through the gateway, which authenticates the caller, checks permissions, applies content policies, records usage, and routes the call to the right provider. You get one place to set policy and one audit trail, no matter how many providers or models are in play.

What is an AI gateway?

An AI gateway is a control plane for model traffic. It presents a single interface to many underlying providers, so client code targets the gateway instead of each provider's own SDK and endpoint. That indirection is what makes governance possible: because every call passes through one layer, you can enforce authentication, authorization, rate limits, logging, and safety checks the same way for all providers, and you can change providers behind the scenes without touching the applications that depend on them.

Key capabilities to evaluate

Capability	Why it matters
Unified provider interface	One API in front of many providers lets you add, swap, or retire a model without rewiring apps.
Centralized credentials	Provider API keys are stored once and never handed to individual developers or apps, ending key sprawl.
Access control	Fine-grained permissions decide which users, teams, and agents can call which models.
Usage and cost tracking	Per-request logging of tokens, latency, and spend gives accurate attribution across every provider.
Rate limits and budgets	Caps on request volume and spend keep any one team or runaway job from exhausting a shared account.
Content policies	Inspecting prompts and responses for sensitive data or unsafe content applies the same rules to every provider.
Traffic routing and fallback	Splitting traffic and failing over to a backup model keeps applications running when a provider degrades.

How Databricks approaches this

Databricks governs multiple providers through Unity Gateway, which became generally available in August 2026. Each external provider is registered as a model provider service, a Unity Catalog securable that holds the connection configuration and API key. The key is stored through an encrypted Unity Catalog connection and attached to requests by the gateway at call time, so consumers authenticate with their own Databricks identity and never see the provider credential. Registering a provider once, centrally, replaces keys copied across notebooks, apps, and developers.
Because model provider services, served models, and MCP services are Unity Catalog securables, you govern them with the same GRANT and REVOKE commands used for tables. EXECUTE lets a principal call a model, READ_METADATA lets them see the service, and MANAGE lets an administrator change its configuration, rate limits, and access. An AI agent inherits governed access to models the same way it inherits access to data.
Applications reach every provider through one OpenAI-compatible endpoint, so switching a model or adding a provider is a configuration change rather than an application rewrite. You can split traffic across models and configure fallbacks to a secondary model if a primary provider fails. Usage tracking records token counts, latency, and status codes by default, inference tables capture full request and response payloads in governed Delta tables, and external-model spend lands in a system table for cost attribution by user, team, and endpoint. Rate limits attach to each provider service, and budgets set spend thresholds so a shared account can't be drained by one workload. Unity Gateway also offers service policies, content guardrails that evaluate prompts and responses and return allow, deny, or ask verdicts. See the Unity Gateway documentation and the general availability announcement.

Use cases

Consolidating shadow AI. When different teams have signed up for different providers, routing everything through the gateway gives security one inventory of what's being called and one set of keys to rotate.
Multi-provider applications. An app that uses one provider for reasoning and another for embeddings reaches both through one endpoint, with unified logging and cost tracking across them.
Agent governance. Agents that call several models get permissions checked per model and every invocation logged, so an agent can only use the models its user is entitled to.
Cost control. Finance and platform teams use per-team budgets and usage tracking to attribute spend and cap it before overruns happen.

FAQs

What does it mean to govern a model provider?

It means controlling access to that provider through one layer: storing its credentials centrally, deciding who can call it, logging every request and its cost, and applying content policies, rather than trusting each application to do so.

Can one gateway front models from different vendors?

Yes. Unity Gateway presents external providers such as OpenAI, Anthropic, and Google through a single OpenAI-compatible interface, alongside models hosted on Databricks.

How are provider API keys protected?

Keys are registered once as part of a model provider service, stored through an encrypted Unity Catalog connection, and attached by the gateway at request time. Individual users and applications never receive the raw key.

How does the gateway help control cost?

It records token usage and spend per request and lets you set rate limits and budgets per provider and per team, so spend is both visible and capped.

Does routing through a gateway require changing application code?

No. Because clients call one OpenAI-compatible endpoint, you can add providers, split traffic, or fail over to a backup model without changing the application.