Accountable AI
AI is treated as a controlled workflow: the decision boundary, evidence, human authority and fallback remain visible.
Trust center
Control is part of the product.
How Technozor approaches accountable AI, information handling and the operational controls that make delivery inspectable.
Trust model
Controls belong where decisions happen.
These statements describe our delivery posture, not a certification claim. Specific contractual, security and regulatory obligations are agreed for each engagement.
Information handling
Data minimisation, approved access and context-appropriate retention are design decisions—not formality after delivery.
Operational controls
Ownership, review, observability and recovery are designed into consequential systems—not appended after launch.
Transparent publication
Public customer evidence and product claims are governed by explicit source, ownership and review metadata.
Control lifecycle
Trust is maintained across the work, not declared at the end.
- 01
Before access
Agree the system boundary, information classes, authorised participants and minimum data needed.
- 02
During delivery
Keep decisions, changes, test evidence and exceptions traceable to the people responsible for them.
- 03
Before operation
Exercise evaluation, human review, fallback, incident and recovery paths against realistic conditions.
- 04
After transfer
Leave named ownership, runbooks, review points and a safe mechanism for changing the system.