AI Backends
AI backends for products that have to stay up
Model calls, workers, and queues live inside your API. The feature keeps working when the model is slow, wrong, or rate-limited.
SaaS teams adding AI to an existing product, not a chat demo.
What the work includes
- Model APIs with timeouts, retries, and usage limits
- Background workers and queues so the request path stays fast
- Auth and tenancy so one customer's data never leaks into another's
- Deploys on GCP, AWS, or Cloudflare, with a handoff your team can run
Production architecture
Production architecture is part of this work: Postgres, auth, multi-tenant APIs, and a deploy your team can own after handoff.
Proof
- BridgeOpsOne
OpenAI-graded training simulators, entitlements, and a security pass before launch.