Architecture Principle · 06 of 9
AI-Ready
Modules don't need to be AI-aware. They emit structured events and expose query contracts. The AI layer consumes them — adding intelligence without forcing modules to know they're being consumed.
What this means
In practice.
AI features can be added without touching individual module code
Same data model powers natural language chat, predictions, and bulk actions
Multi-model architecture — switch between Claude, GPT, Gemini per deployment
AI access governed by same RBAC as humans — no permission elevation through AI
How it works
Under the hood.
Module contracts
Each module publishes its data schema as a structured contract (JSON Schema).
Tool registry
AI layer registers tools that map natural language requests to module API calls.
RBAC inheritance
AI executes calls under user's identity. If user can't access data, AI can't either.
Audit trail
Every AI-driven action audit-logged separately with original prompt + reasoning.
Visual
Real-World Example
Real-world: New analytics with no module changes
Before
Customer asked for 'predict which orders are at risk of late delivery'.
After
AI team trained the model using existing order, dispatch, and production data. No changes to Sales or Production modules. Deployed in 2 weeks. Predictions accessible via chat and dashboard.
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