Canonical

The semantic infrastructure beneath operational AI.

Canonical is an independent AI consultancy. I'm Fahad Baig, the founder and principal. I design and build canonical models, retrieval systems, and agentic workflows for organizations where generic AI patterns don't hold. Hands-on, senior-led, scaled with named collaborators when the work requires it.

Start with an architecture review

What I work on

Four overlapping domains. Most engagements touch more than one.

  • 01

    Semantic infrastructure

    Canonical models, entity resolution, taxonomies, and ontologies. The representation of the business that production systems can actually use.

  • 02

    Retrieval and graph systems

    GraphRAG, hybrid retrieval, internal search, MCP servers. Structured retrieval over canonical models, not vector search alone.

  • 03

    Agentic workflows

    Governed agents with explicit human-in-the-loop checkpoints. Operational copilots embedded in real workflows, not standalone chatbots.

  • 04

    Deployment engineering

    Ingestion, evaluation harnesses, observability, and rollout patterns on Databricks, Snowflake, or your existing data platform.

See full capabilities

Most operational AI doesn't fail at the model. It fails at the representation.

If your organization is operating in classification-heavy, data-fragmented, or regulated environments, and you're past the pilot phase but production reliability is harder than the demos suggested, start with an architecture review.

Start with an architecture review