SDLC / Requirements / Assurance

Enterprise AI implementation

Translate AI ambition into a controlled delivery lifecycle with explicit requirements, evaluation criteria, release decisions and ongoing ownership.

Implementation lifecycle

Problem statement, stakeholder mapping, use-case assessment and baseline metrics.

Functional, non-functional, privacy, security, governance and human-oversight needs.

Model and vendor evaluation, data flows, integration and fallback design.

Evaluation sets, failure modes, red teaming where appropriate, acceptance gates.

Change control, training, user communications, monitoring and rollback.

Cost, quality, drift, incidents, periodic review and measurable benefits.