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Explore at your own pace.

Prefer to read first? Each path is one paper, one worksheet exercise and an optional Studio exercise. None of it is required to request a working session.

All resources are free. Use made-up examples, not client data.

A route through the resources

Executives and accountable owners

Decide what to fund and what a release must demonstrate.

  1. Read with a decision in mind

    Why Enterprise AI Stalls After the Demo. Read for the gap between a demonstration and an operating capability.

  2. Make the question concrete

    Use the readiness worksheet with the business owner, technical lead and control owner. Record three gaps, evidence needed and the person responsible for each.

    Open the readiness worksheet

  3. Try it in Ontology Studio

    Create a small glossary for one workflow. Define a term people disagree about and record the source and question it must help answer.

    Open Ontology StudioRead the documentation

  4. Discuss the next decision

    Bring one workflow, a measurable outcome and your three most consequential gaps.

    Explore starting engagementsRequest a working session

A route through the resources

Architects and technical teams

Make meaning, evidence and authority inspectable before connecting tools.

  1. Read with a decision in mind

    The Four-Part System. Read for the separate responsibilities of information, interfaces, controls and operation.

  2. Make the question concrete

    Sketch one request from the caller to the authorized source and back. Mark where meaning is resolved, permissions are checked and the result is tested.

    Open the readiness worksheet

  3. Try it in Ontology Studio

    Model one topic your system depends on. Add the terms, relationships and sources, then export the result as context for the AI tool your team uses.

    Open Ontology StudioRead the documentation

  4. Discuss the next decision

    Bring the request sketch, an authorized architecture summary and the release evidence you are missing.

    Explore starting engagementsRequest a working session

A route through the resources

Risk, compliance and audit reviewers

Know what to ask for before an AI workflow goes live.

  1. Read with a decision in mind

    AI Governance Evidence. Read for what reviewers at US banks and insurers inspect, and the records that answer them.

  2. Make the question concrete

    Use the readiness worksheet on one workflow with its business owner and technical lead. Mark each control as evidenced, partial or missing, and name who closes each gap.

    Open the readiness worksheet

  3. Try it in Ontology Studio

    Build a short glossary of the terms your policy relies on, such as model, use case and material change. Link each term to the policy wording it comes from.

    Open Ontology StudioRead the documentation

  4. Discuss the next decision

    Bring the worksheet results and the evidence you would expect to see before approval.

    Explore starting engagementsRequest a working session

A few distinctions to keep clear

Ontology and business meaning
Types of things, their definitions and relationships, within an explicit scope.
Evidence
The sources and passages that support a claim, with enough provenance to inspect it.
Executable logic
The formulas, queries and services that calculate results. Editing a definition does not rewrite these calculations.
Authority
What a caller and service are permitted to read or do. Enforce this in the systems performing the work.
Explore all whitepapersOpen the primer and workshop