Production AI standard

Useful automation has to be controllable.

Security is a set of decisions around your workflow—not a badge on a slide. We make data movement, model behaviour, approvals and recovery paths explicit before production.

Map before build

We document systems, data classes, decision points and failure modes before choosing the automation path.

Least privilege

Connections are scoped to the smallest practical set of records and actions, with separate credentials where appropriate.

Human authority

High-impact or low-confidence outputs pause for an accountable person. AI assists; your team owns the decision.

Observable operation

Important steps, errors and hand-offs are logged so a workflow can be monitored, investigated and improved.

Tested releases

Representative evaluation cases, edge cases and acceptance criteria are agreed before a production change.

Controlled recovery

Retries, fallbacks, rate and cost limits, alerting and a named recovery path are designed into the workflow.

Control lifecycle

Production readiness from discovery to operation.

01

Discover

Data-flow map, risk classification, success metric and ownership.

02

Design

Permissions, model/provider choices, retention, approvals and fallback behaviour.

03

Validate

Test dataset, failure cases, quality thresholds and stakeholder acceptance.

04

Operate

Monitoring, change record, incident path, reviews and improvement backlog.

What gets agreed for your build

System and data ownership
Provider and retention choices
Access and secret management
Human approval boundaries
Quality and confidence thresholds
Logging and alert recipients
Failure and manual fallback path
Documentation and change control