Best AI gateway solutions

Summary

• An AI gateway is the control plane in front of every model and agent call, so the best solution turns scattered model traffic into something you can govern, route, observe, and pay for on purpose.
• The strongest solutions go beyond proxying requests: they enforce access control, apply safety and PII guardrails, cap spend, and log every call across many model providers.
• Solutions come in four shapes: single-cloud gateway, an assembled stack of separate tools, a custom in-house build, or a platform-native gateway that governs AI with the same model as your data.
• On Databricks, Unity Gateway is the platform-native control plane, built on Unity Catalog and generally available as of August 2026, governing AI across asset, traffic, and behavior layers.
• It gives unified access to Databricks-hosted and external models, Unity Catalog access control, rate limits, payload logging, budgets with hard spend caps, and traffic splitting with fallbacks.

Best AI gateway solutions

An AI gateway is the control plane that sits in front of every model and agent call, so the best AI gateway solution is the one that turns scattered model traffic into something you can govern, route, observe, and pay for on purpose. The strongest solutions do not stop at proxying requests; they enforce access control, apply safety and compliance rules to prompts and responses, cap spend, and log every call across many model providers. For an enterprise, the deciding factor is usually whether the gateway plugs into the governance you already run on your data, or forces a separate policy model just for AI. On Databricks, that control plane is Unity Gateway, built on Unity Catalog.

What is an AI gateway?

An AI gateway is a centralized enforcement layer for model and agent traffic, much like an API gateway for traditional applications but built for the demands of AI. Applications and agents call the gateway instead of calling models directly. It authenticates the caller, checks policy, routes the request to the right model (hosted in-house or from an external provider), applies guardrails to the input and output, records the exchange, and meters the cost. That single point of control is what makes governance, observability, and cost management possible.

AI gateway solution approaches

Teams generally reach for one of four approaches. The right one depends on how many providers you use and how tightly AI must align with data governance.

Approach	What it means	Trade-off to weigh
Single-cloud gateway	Standardize on one cloud provider's AI stack	Governance is optimized for that provider's ecosystem
Assembled stack	Combine separate gateway, guardrail, policy, identity, and observability tools	Flexible, but you integrate and maintain the seams yourself
Custom-built	Build routing, policy, and logging in-house	Full control, with ongoing engineering and operational ownership
Platform-native	Use the gateway built into your data platform	AI is governed with the same model as your data, in one place

What to look for in an AI gateway solution

• Provider-agnostic access to models hosted in-house and from external providers, so teams are not locked to one vendor.
• Access control that reuses your existing permission model instead of a separate one for AI.
• Guardrails that filter unsafe content and detect sensitive data such as PII on requests and responses.
• Rate limits and fallbacks to protect capacity, cost, and availability.
• Full request and response logging in one governed, queryable place, plus budgets with hard spend caps.

How Databricks approaches AI gateway solutions

Unity Gateway is the platform-native option: the control plane for enterprise AI, built on Unity Catalog and generally available as of August 2026. Because it is part of Unity Catalog, it governs AI along three layers. Asset governance registers models, MCP servers, functions, and connections as securable objects with the same privileges you use for tables. Traffic governance routes and rate-limits every request from one control plane. Behavior governance uses service policies to allow, deny, or require approval for individual requests and responses based on the caller and the content. See how AI governance works on Databricks.
Concretely, Unity Gateway gives a unified API across external providers such as OpenAI, Anthropic, and Google alongside Databricks-hosted models. Access uses standard Unity Catalog privileges (EXECUTE to use a model or tool, CREATE and MANAGE to register and administer), extended by ABAC GRANT policies that key off tags such as provider or approval status. Rate limits cap tokens and requests per principal, with the option to set tighter limits for service principals. Payload logging writes full requests and responses to Unity Catalog Delta tables for audit and debugging. Budgets support per-user thresholds and hard spend caps that block further calls when a limit is hit, and traffic splitting and fallbacks distribute load and reroute automatically if a model degrades. LLM guardrails and service policies, which filter safety and PII and enforce custom rules, are in Beta; test policies in log mode before enforcing them. Start with AI governance with Unity Gateway.

Use cases

Multi-provider standardization. A team using several model providers routes them all through one gateway, so access, logging, and budgets stay consistent across every model.
Safe agent rollout. Before an agent reaches production, guardrails screen inputs and outputs for unsafe content and PII, and service policies require approval for sensitive tool calls.
AI cost control. Finance and platform teams attribute spend by user, team, and application, then set budgets and hard caps so a runaway workload cannot blow through the AI budget.

FAQs

Does an AI gateway lock me into one model provider?

A good one does the opposite. Unity Gateway gives a single governed entry point to models hosted on Databricks and to external providers, so you can add or change models without a separate access model per provider.

How does an AI gateway control AI cost?

Through two layers. Rate limits cap traffic volume per user or endpoint, and budgets set spend thresholds with hard caps that stop calls once a limit is reached. Full usage logging then attributes cost by user, team, and application.

Is Unity Gateway generally available?

Unity Gateway is generally available as of August 2026. Core capabilities including model services, rate limits, budgets, and payload logging are GA, while LLM guardrails and service policies are in Beta.