Intelligence & AI Engine

Responsibilities

• Provide model routing, inference, embeddings, and agent/tooling hooks.
• Enforce safety controls and evaluation gates.
• Manage prompt/tool contracts and telemetry for AI systems.

Key interfaces

• Model selection/routing policy and fallback strategy.
• Tool invocation contracts and sandbox boundaries.
• Evaluation harness and red-team test suites.

Operational signals

These are the measurements that tell you whether this layer is healthy in production.

• Cost per request, latency per model, and fallback frequency.
• Safety filter triggers and refusal rates.
• Quality metrics from offline evaluations (as configured).

Failure modes

• Hallucination/unsafe output without guardrails.
• Prompt/tool drift breaking integrations.
• Unbounded costs during spikes.

Production readiness checklist

• Define safety policies and log tool/model decisions.
• Add evaluation gates for changes to prompts/tools/models.
• Implement budgeting (per-user/per-tenant) and circuit breakers.