AI Security &
Risk Management

Prompt injection is an attack where a malicious user crafts inputs that manipulate an LLM into ignoring its instructions and executing unintended actions — such as leaking private data, bypassing safety filters, or generating harmful content. As LLMs are embedded in more enterprise workflows, prompt injection becomes a significant security risk that requires dedicated hardening.

GDPR compliance for AI involves multiple layers — ensuring personal data used in training is lawfully processed and minimised, implementing the right to erasure for training data, documenting AI decision-making for explainability requirements, and conducting Data Protection Impact Assessments (DPIAs) for high-risk AI processing. We map each requirement to specific technical and process controls.

AI bias occurs when models produce systematically different outcomes for different demographic groups — leading to unfair decisions in hiring, lending, customer service, or other high-stakes applications. Our bias auditing evaluates model outputs across demographic dimensions, identifies sources of bias in training data or model architecture, and implements mitigations to ensure fair treatment.

The EU AI Act classifies AI systems by risk level and imposes requirements accordingly. High-risk AI systems (used in employment, credit, critical infrastructure) require conformity assessments, transparency documentation, human oversight mechanisms, and registration. We help organisations understand their classification, implement required controls, and maintain compliance documentation.