Deployment

This page shows how TurfAI's services fit together in production and where to find the operational runbooks.

TurfAI is a set of services that work together: the DMS/API layer (Strapi), a job router (Redis) and processors, an LLM service, the RAG query service, the event bus, and the document store (PostgreSQL + pgvector, plus GCS for files). It runs as managed SaaS, in your own AWS, Azure or GCP account (BYOC), on-prem inside your perimeter, or at the edge on Jetson Orin NX.

Service topology

The frontend and the MCP server talk only to the DMS (port 1338) — never directly to the Python services. The DMS routes jobs through Redis to the processors, which call the LLM/RAG services and integrations.

Operational references

Deployment runbooks — environment configuration, go-live checklists, backup and restore — are shared with your team during the engagement, tailored to the deployment model you choose.