NOTETo set up an LLM Provider, navigate to Settings → Integrations and click Add New Integration. LLM Provider integrations are managed by organization admins.
How it works
- Register a provider with its endpoint and credentials, and select which models to expose. For most providers, Datafold fetches the available model list automatically once credentials are entered.
- Models appear in every model picker — goal creation, project defaults, per-role overrides, and the PM assistant — labeled with the integration name.
- Credentials are resolved at request time. Nothing is baked into a goal: editing an integration’s key or endpoint takes effect on the next agent request, without recreating goals.
- Credentials are encrypted at rest and never returned by the API — secret fields are masked on read and kept unchanged when a masked value is re-submitted.
- Costs are tracked automatically. Token usage and estimated spend per model appear in goal cost breakdowns and count toward goal budgets.
Supported providers
OpenAI-compatible (universal)
OpenAI
Anthropic
Google Gemini
Azure AI Foundry
AWS Bedrock
Google Vertex AI
Databricks
Snowflake Cortex
/chat/completions protocol — Together, Fireworks, Groq, OpenRouter, Mistral, vLLM, LM Studio, Ollama, and most other inference services — works through the universal OpenAI-compatible provider.
