Make trust part of how your enterprise works.

Trust follows the work.

An identity check cannot explain whether an action serves the business. A model evaluation cannot grant permission to change a record. An audit log cannot undo an unintended effect. Contextual Trust is our proposed cross-layer security and trust capability for the CAE approach: connect purpose, identity, information, decisions, execution and operational evidence around a real workflow.

Start with your organisation’s existing controls and stack. Identify where trust depends on a missing definition, unclear owner, stale source, over-broad permission or untested recovery path. Turn those findings into a prioritised architecture and delivery plan, while preserving the capabilities that make your enterprise competitive.

Explore the introductory assessment

The assessment opens on the separate Contextual Trust website. It uses self-reported answers and rules, with its own organisation and email registration, manual verification and privacy arrangements. It provides an introductory discussion starting point; it does not inspect your estate, certify compliance or grant agent permissions.

Eight views. One accountable workflow.

The following are proposed trust review views across the CAE capability architecture, rather than a new canonical layer model. Apply them to a bounded business journey and its dependencies.

Trust depends on the connections between these views. A workflow can have strong authentication and still act on the wrong source, exceed its delegated scope or repeat an unknown transaction after a timeout.

Understand first. Enforce through the actual system.

Discovery can produce a reviewed account of controls, evidence gaps, dependencies and proposed actions. AI may assist with drafting and analysis where access, handling and evaluation are agreed. People validate material findings and retain risk and release decisions.

Enforcement requires implemented integrations. Identity providers must establish identity; policy gates must receive trustworthy inputs; adapters and target systems must constrain effects; operational owners must test monitoring, stop and recovery paths. A diagram, readiness answer or generated report does not install those controls. Where suitable, a later delivery increment can connect and evaluate them within an explicitly approved scope.

See a governed execution example · Inspect the enterprise model

Measure trust where it matters.

Agree baselines and thresholds for the workflow before delivery. Useful candidate measures include:

• Context coverage: proportion of material sources with a named owner, provenance, access basis and freshness rule; record the denominator and unassessed sources.
• Authority coverage: proportion of consequential action paths with enforced identity, scope and policy checks, and bound approval where required.
• Evaluation performance: supported and unsupported task outcomes against agreed cases, including adversarial inputs and important user groups. Record uncertainty and failure severity.
• Execution integrity: duplicate effects, unknown transaction results, reconciliation time and recovery success under exercised failure cases.
• Operational control: time to detect, stop and recover from an incident; evidence completeness and overdue exceptions.
• Business value and cost: useful outcomes, user adoption and total operating cost, including human review and support effort.

These are proposed measures, not reported product results. Set organisation-specific definitions and owners. A single trust score can hide a critical unresolved constraint.

What is available now

This site provides architecture explanations, fictional models and visualisations, an email enquiry route, and a link to the separate introductory Contextual Trust assessment. A human-led enterprise health check, responsible AI readiness review or discovery engagement is subject to agreed scope, access, availability, timing, pricing and terms.

Customer-connected discovery, automated enterprise evidence collection, live policy enforcement, continuous control monitoring and agent execution are future implementation work, requiring separate design, integration, evaluation and authority. This release does not provide those services or claim customer security outcomes.

Discuss your enterprise health and trust priorities

Explore enterprise health and AI readiness · Review current capability status · Privacy and use