Deploy where the data belongs.
Private AI and application systems can be built in the client's cloud account, VPC, or hardware. Residency and access requirements are specified for the engagement.
SecurityACYCLIC / SECURITY
The boundary
comes first.
Data handling and AI use are design inputs, not an afterthought. The controls for a specific system are agreed with the client before implementation.
Controls and responsibilities are defined for each engagement.
For each engagement, we identify where data resides, which people and systems may access it, what model calls occur, and what evidence the client needs to inspect. These decisions shape architecture, evaluation, and deployment.
Make inference inspectable.
For model deployments, we plan evaluation suites, inference audit trails, and version pinning so teams can examine behavior and know which model produced an output.
Keep consequential decisions legible.
We identify where model output needs review and where a person must retain the decision. Failure paths and exception handling belong in the workflow.
Document the implemented controls.
Acceptance criteria cover the system as deployed. The actual boundaries, access model, and operational responsibilities are recorded with the client.
DISCUSSION SCOPE
Bring your requirements early.
Tell us about data classification, hosting limits, model restrictions, review requirements, and the system that will own the record. We can then define a feasible delivery boundary. The required controls are part of the delivery discussion.
NEXT STEP
Discuss an engagement Discuss the deployment boundary.
Tell us the system, the constraint, and the deadline. We will tell you if we can take responsibility for the result.