RUBIKSCORPRUBIKSCORP · Pune, India
AI System Audit
Find reliability and workflow problems in the AI your business already uses.
What we can review
The final test plan is agreed for your system and business risks.
Answer quality
Are answers accurate, supported by sources and appropriate for the user’s request?
Data access and misuse
Can requests expose data or cause a tool to act beyond the intended permissions?
Workflow reliability
Where do tools, handoffs and error handling fail? How do latency and repeated calls affect the journey?
What your team receives
A decision document your team can use after the engagement.
- A summary of the scope, test approach and limitations.
- Documented findings with examples and likely business impact.
- Prioritized recommendations and a proposed improvement sequence.
- A walkthrough of the findings and open questions.
What we need to begin
An overview of the system, the user journeys that matter and access to agreed test material. Use synthetic or minimized data where possible. We agree confidentiality and access arrangements before reviewing private systems.
1. Define the scope
We discuss your system, the problem and the evidence available. Scope, fees and access are agreed before work begins.
2. Review and test
We examine agreed journeys or operating conditions, document failures and assess their likely business impact.
3. Decide what to improve
You receive prioritized findings and recommended next steps. Implementation and ongoing monitoring are scoped separately.
What an audit can establish
An audit reports the behavior observed within its scope. It does not certify compliance, prove that an AI system is safe in every situation or guarantee that future failures will not occur.