API Access
Integrate Steinkauz inference into your applications with OpenAI-compatible HTTP endpoints. Use the same models, provider configuration, and subscription budget as the chat UI.
What API Access includes
Programmatic access to the full Steinkauz platform stack — not a separate product tier.
Platform capabilities
- OpenAI-compatible endpoints: POST /v1/chat/completions and GET /v1/models
- Steinkauz-issued API keys with create and revoke in Settings
- Same gateway or BYOK routing, security classifications, and inference budget as chat
- Usage attribution per key in your usage statistics (chat vs API)
Who it's for
- Automation and internal tools that need reliable multi-provider inference
- Agent and orchestration layers built on top of Steinkauz
- Existing codebases using the OpenAI SDK — change base_url and go
- Teams that want both a chat UI for humans and an API for systems
Quick start
Create an API key in the chat app, then call the endpoints with any OpenAI-compatible client.
- Sign up and subscribe to a Steinkauz plan.
- In the chat app, go to Settings → API Keys and create a key (shown once — store it securely).
- Point your client at the Steinkauz base URL and send a chat completion request.
# Steinkauz Platform API example (OpenAI-compatible HTTP API)
# List models and pick any. For this example, we're picking the first entry of the list.
MODEL=$(curl -sS "$STEINKAUZ_BASE_URL/v1/models" \
-H "Authorization: Bearer $STEINKAUZ_API_KEY" | jq -r '.data[0].id')
# Send a chat completion
curl -sS "$STEINKAUZ_BASE_URL/v1/chat/completions" \
-H "Authorization: Bearer $STEINKAUZ_API_KEY" \
-d "{\"model\": \"$MODEL\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello 👋\"}]}"Get started with API Access
Sign up, create an API key, and integrate Steinkauz into your stack. Full reference in the docs.