Layers, flows, and components of the AI Fabrick (Overseer, Router, Proctor, Workers, Auditor).

Architecture

Layers

  1. Overseer (Orchestrator)
    • Plans execution, manages continuations, routes tasks.
  2. Router
    • Decides whether to run local (light) or heavy (RunPod/Docker).
  3. Proctor
    • QA checks: schema validation, safety rules, acceptance tests, thresholds.
  4. Workers
    • Light = provider wrappers (OpenAI/Gemini/DeepSeek) in Next.js.
    • Heavy = RunPod/Modal containers for GPU/long pipelines.
  5. Auditor
    • Logs decisions/events to Redis + S3 for reproducibility.

Execution Flow

sequenceDiagram
    participant User
    participant Overseer
    participant Router
    participant Worker
    participant Proctor

    User->>Overseer: Submit Prompt
    Overseer->>Router: Decide tier
    Router-->>Overseer: local / heavy
    Overseer->>Worker: Run task (stream)
    Worker-->>Proctor: Output
    Proctor-->>Overseer: QA pass/fail
    Overseer-->>User: SSE events + results

Decision Policy

Signals scored by the Router:

  • Duration forecast: > soft budget → heavy/continuation
  • Capability needs: GPU, long-context, tools → heavy
  • Safety risk: high → heavy proctor or human-in-loop
  • Latency target: interactive → prefer local
  • Cost ceiling: avoid overage
  • Reliability: select environment with better quotas
  • Data governance: PII/export constraints may force local