AI System Audit
Identify personal-data leakage, prompt-injection exposure and model-retirement risk in AI code.
- Timeline
- 1-3 weeks
- Engagement
- Fixed-scope audit
- Practice
- Assure
The situation
AI features shipped fast. Now you need to know where they can leak personal data, follow instructions hidden in user input, or fail quietly when a vendor retires a model.
What we deliver
- [01] Scan of every LLM call site in your codebase
- [02] Findings ranked P0, P1 and P2 with file and line
- [03] Fixes for the highest-risk findings
- [04] Re-audit after the fixes land
Start here
Have a problem AI might solve?
Describe the outcome you need. Within two working days you receive a written view on whether AI is the right tool, the risks to manage, and a proposed first step.