Scope before access
Agree what systems, metadata, artifacts and environments are required. A marketing integration diagram does not authorize access to a tenant.
Security & trust
Trust must be proven at the right boundary.
Production AI assurance involves sensitive system state, evidence and human decisions. A secure evaluation starts by defining scope, authoritative sources, permitted access and the controls the buyer needs to verify.
Assurance design
Four distinctions the platform must preserve.
Evidence provenance
Evidence needs a source, version, recorded time and clear validity status. Unsupported or stale information remains visible.
Human approval
Readiness and automated revalidation are not substitutes for an authorized reviewer decision.
Auditable state
Approved baselines and subsequent review events must be distinguishable so a decision can be reconstructed and challenged.
Enterprise evaluation
Validate implementation and security evidence, not a checklist of promises.
The exact controls, hosting model, and release qualifications applicable to a customer must be confirmed before a pilot proceeds.
Identity and permissions
Review authentication, user roles, authorized actions and environment boundaries required for your deployment.
Data handling
Determine precisely which configuration and evidence may be collected, stored, retained and deleted.
Hosting and isolation
Agree architecture, tenant/environment isolation and service operation requirements before connecting real systems.
Control evidence
Request actual relevant test reports, security policies, deployment and incident practices rather than relying on marketing labels.
Bring your security requirements to the first conversation.
We can discuss integration scope and identify the evidence needed before any production access is requested.