Access & data boundaries
Role-aware access, tool permissions, credential handling, and approved information flows.
Capabilities / Security, Governance & Reliability
Design access, evaluation, observability, and oversight into the AI systems and infrastructure being commissioned.
Engineering mandate
Enterprise intelligence introduces new trust boundaries between data, models, tools, and people. A convincing output is not enough: the organization needs to understand what actions are permitted, what evidence is recorded, and how failures are handled.
The engineering scope should define the threats, data sensitivity, operating requirements, and controls relevant to the use case. Testing depth, assurance obligations, and specialist review are agreed rather than implied by a general service description.
Technical scope
Architecture considerations
Role-aware access, tool permissions, credential handling, and approved information flows.
Quality criteria, representative failure scenarios, and scoped security assessments.
Task records, model and tool activity, review checkpoints, and traceable system behavior.
Escalation, recovery, incident responsibilities, and ongoing review arrangements.
Concrete outputs
Outputs, acceptance criteria, ownership, provider dependencies, and operating responsibilities are agreed in the statement of work.
Illustrative enterprise applications
Application area to assess through discovery and a representative evaluation.
Application area to assess through discovery and a representative evaluation.
Application area to assess through discovery and a representative evaluation.
Application examples describe intended uses, not completed customer engagements.
Share your context, systems, and the capability you need to develop.