01 / AI platforms · reference
Multi-agent platform with an eval loop
Lots of agents, one engine running them, and every model or vendor behind an interface. Traces go to an eval runner, and its verdict decides whether a release ships, so changing a prompt gets the same care as changing a schema.
Load-bearing decisions
- Providers are ports chosen by environment, never imported by feature code; swapping OpenAI for a private Azure endpoint is a config change.
- Every model call emits an OpenTelemetry span with cost and latency; a sample is scored against golden sets and drift is a release blocker.
- Guardrails run on the way in and on the way out of the router, not inside individual agents.
- Tools execute in a sandbox with allowlists and TTLs; the agent never holds a credential.
- One image runs on Cloud Run, AKS, or Container Apps; the WAF, private endpoints, and CMK are part of the Terraform, not a checklist.
TypeScript · NestJS · AI SDK · MCP · pgvector · Mem0 · OpenTelemetry · Terraform · Kubernetes