Trustworthy AI

The challenge

AI models and assistants are being connected to business data and systems faster than they are tested. An unvalidated model can leak sensitive data, be manipulated into harmful actions, or give wrong answers that people trust.

What you get

• Security testing of AI models before and after launch — attempts to extract sensitive data, bypass instructions or trigger actions nobody approved
• Validation of model outputs for accuracy, bias and harmful content against agreed test cases
• Checks on the data going in, so sensitive or manipulated data doesn't reach the model
• Guardrails and human approval for high-stakes actions
• Ongoing monitoring that flags misuse, drift and new weaknesses after go-live
• Clear validation reports for security teams, boards and regulators, aligned to recognised AI risk management frameworks