Service
Governance and evaluation for organizations that cannot afford sloppy deployment.
Many AI failures are not model failures alone. They are failures of evaluation design, workflow boundaries, monitoring, documentation, and accountability. This service is built for teams that need reliability and defensibility, not just novelty.
Evaluation design
Define quality criteria, benchmarks, failure modes, and decision thresholds.
Governance controls
Clarify oversight roles, auditability, and usage boundaries.
Monitoring discipline
Track drift, exception patterns, and ongoing operational performance.
Practical governance tool
Use the AI Governance Checklist for Mid-Market Teams to turn ownership, scope, data, evaluation, monitoring, and release requirements into a working control review.