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What an OpenAI-Compatible API Router Should Actually Do

#ai #programming #webdev

An OpenAI-compatible API router should not make your stack more complicated. If it does, it has already failed.

The whole point of compatibility is boring simplicity:

One base URL.

One API key.

Same general SDK shape.

That gives you room to improve the economics without rewriting the application.

For AI coding workflows, this matters because the tool in front is often already good enough. The pain is underneath: cost, provider management, usage logs, and routing.

The minimum useful setup should look familiar:

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://incat.ai/v1",
  apiKey: process.env.OPENAI_API_KEY,
});
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If a router requires a large rewrite before you can test it, most developers will not bother. They are right.

The first test should be small:

  • one workflow
  • one API key
  • one prepaid balance
  • one cost comparison

What should the router do?

Route by task

Send routine work to cheaper capable models. Keep risky work on stronger models.

Preserve logs

Developers need to know which workflow burns money.

Avoid surprise bills

Prepaid credits are useful because they turn runaway usage into a visible constraint.

Keep escape hatches

If a cheaper route is not good enough, switch back. Routing should create options, not lock-in.

That is the category I want inCat to live in.

Not another AI coding app.

Not a model museum.

An OpenAI-compatible API router for developers who want the same workflow to cost less.

Generate a config:

https://incat.ai/codex-config-generator.html

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