What we test when the risk warrants it
- Accuracy. Does it get the answer right, consistently?
- Robustness. Does it hold up under noise, edge cases and drift?
- Bias. Does it treat people and groups fairly?
- Prompt injection. Can hidden instructions take control?
- Data leakage. Can it be made to reveal what it shouldn't?
- Tool misuse. Can it be steered into harmful actions?
- Unsafe autonomy. Does it act beyond its mandate?
- Human escalation. Does it hand off when it should?
What you get
- Chatbot and conversational AI evaluation: accuracy, escalation and failure modes
- Prompt injection and data-leakage testing
- Bias and robustness checks
- Retesting and evidence for sign-off
Harms first, then scenarios
Testing is planned from the harms that matter for your system and the people it affects, then translated into test scenarios. Each finding is traceable to the scenario that produced it and the control it tests, so results can be rechecked after fixes and carried into your governance records.
Scope and independence
Testing is scoped to the system, its risk and its deployment context, and agreed in writing before it starts. Results reflect the system as tested at that time; they are evidence for your decision-makers, not a guarantee or a certification.
A sample assessment and test report is available on request. Ask for a copy.
