What an AI API gateway does
An AI API gateway sits between your application and model providers. It gives the application one stable endpoint while handling authentication, protocol translation, routing, retries, and usage records behind the scenes.
This separation matters because model catalogs and provider relationships change faster than most product code should. The gateway keeps those operational decisions outside the application itself.
The value of one key
Managing a separate credential for every provider creates operational work: secrets must be distributed, rotated, monitored, and removed consistently. A unified buyer-side key creates one control point for access and spend.
- Centralize credential rotation and revocation.
- Apply budgets and rate limits consistently.
- Compare usage across models with one reporting format.
- Switch routing paths without shipping new application code.
What to evaluate before choosing a gateway
Protocol compatibility is only the starting point. Check whether the gateway preserves streaming, tool calls, structured outputs, image inputs, and provider-specific features your product relies on. Also examine how it handles retries, request identifiers, error responses, and model availability.
A good gateway should make the common path simple without hiding the operational evidence needed to debug production traffic.
A low-risk migration path
Start with one non-critical workload and a model your application already uses. Change the base URL and credential, verify response behavior, then compare latency, success rate, and cost. Expand traffic gradually once the gateway behaves consistently under your real workload.
Use one DIT key to access supported models through a market of qualified AI providers.
Get your API key