API key management for AI apps

Who it is for

Teams that need server-side API credentials, separated app environments, usage review, and a clear trial-to-prepaid workflow.

Use cases

• Server-side SaaS integrations.
• Agent runtime credentials.
• Internal automation keys.
• Testing keys for staging environments.
• Usage review before production rollout.

How InferGate helps

Create an account, generate an API key in the dashboard, configure your compatible client, then review usage and credit movement as requests run.

Base URL

https://api.useinfergate.com/v1

curl example

curl https://api.useinfergate.com/v1/models \
  -H "Authorization: Bearer YOUR_INFERGATE_API_KEY"

JavaScript example

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.INFERGATE_API_KEY,
  baseURL: "https://api.useinfergate.com/v1"
});

const models = await client.models.list();
console.log(models.data.map((model) => model.id));

Python example

from openai import OpenAI
import os

client = OpenAI(
    api_key=os.environ["INFERGATE_API_KEY"],
    base_url="https://api.useinfergate.com/v1",
)

models = client.models.list()
print([model.id for model in models.data])

Trial credits and pricing

New accounts currently include $20 in trial credits. Use prepaid API credits when ready to scale. Pricing depends on selected model/provider route and dashboard configuration.

FAQ

Where do I create keys?

Create and manage API keys in the InferGate dashboard.

Should I put keys in frontend code?

No. Keep API keys on your server or secure runtime environment.

Can I test without paid credits?

New accounts currently include $20 in trial credits.

What should support tickets include?

Account email, request ID, endpoint, model name, approximate request time, and error message.