Business purpose first
We define the intended business outcome and success measure before selecting models or agent patterns. Deterministic automation is preferred when a task does not require probabilistic AI.
Human oversight
We design review, approval, and escalation controls based on the consequences of an error. High-impact decisions should not be delegated to an AI system without appropriate human accountability.
Data protection
Implementations should minimize data collection, restrict access, separate environments, and use providers appropriate to the sensitivity and contractual requirements of the information involved.
Reliability and transparency
AI outputs can be incomplete or incorrect. Systems should communicate material limitations, ground outputs where practical, monitor failures, and provide recovery paths instead of presenting uncertainty as fact.
Evaluation and improvement
Production AI should be evaluated against representative tasks and monitored using business, quality, safety, and cost signals. Material changes should be tested before broad release.
Client responsibilities
Governance is shared. Clients remain responsible for lawful use, source-data rights, domain-specific compliance, authorized users, and final decisions made using AI-assisted outputs.