Validate critical journeys
Exercise the customer and operational journeys that matter most to the business, including edge and recovery paths.
- Critical business journeys
- Failure and recovery paths
- Realistic multi-turn execution
Assess whether an AI agent is ready for production across behaviour, business rules, execution integrity, security and release evidence.
Production readiness is not established by a model benchmark or a single evaluation score. It requires evidence that the complete system behaves correctly under realistic journeys and that critical risks are controlled.
Exercise the customer and operational journeys that matter most to the business, including edge and recovery paths.
Check answers, business rules, tool calls, authorization, state transitions and terminal outcomes using the right evaluation method for each claim.
Test high-risk trust boundaries and verify whether adversarial inputs can cause unsafe tool use, policy violations or harmful side effects.
Connect findings and evidence into a governed release assessment that can be reviewed and repeated after changes.
It means the AI system has evidence supporting required behaviour, business correctness, execution integrity, security and operational controls for its intended production scope.
No. A high semantic score does not prove business correctness, execution integrity, authorization, security or successful completion of the intended goal.
Yes. The assessment can become a repeatable regression and release-assurance workflow tied to new builds and release candidates.
Bring one business journey and see how Shyena maps, tests, evaluates, secures and connects the evidence to release decisions.
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