Reference architectures
Artefacts over claims.
We share architecture patterns that we have used in production. These are not theoretical—they represent approaches we have implemented and operated.
Production-tested architectures
Canonical data model layer
A shared semantic layer that enables reuse across capabilities. Business terms mapped to technical implementations. Versioned, documented, governed.
Bronze/Silver/Gold pipelines
Progressive data refinement with validation at each stage. Raw data (bronze) through cleansed (silver) to business-ready (gold). Clear contracts between stages.
Validation and controls
Rules applied at ingestion and transformation. Schema validation, business rule checks, anomaly detection. Bad data rejected early.
Governance integration
Ownership, lineage, and access controls built into the platform. Not bolted on later. Governance that enables rather than blocks.
AI consumption patterns
Query-ready interfaces for analytics. Embedding-ready corpora for retrieval. Safe agent patterns over governed data. AI that operates within guardrails.
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