Risk, Ethics & Compliance
"Make every AI system defensible — to regulators and customers"
Responsible AI governance, model risk management, and regulatory compliance engineered in from day one across the AI delivery lifecycle.
Six controls layers
Model risk framework
Tiered risk classification, validation, monitoring, and decommissioning policies.
Bias & fairness
Bias testing across protected groups, mitigation strategies, ongoing monitoring.
Explainability
SHAP/LIME on tabular models, attention/citation on generative — appropriate to the use case.
Audit trails
Immutable logs of inputs, decisions, and human overrides for regulatory review.
Regulatory mapping
EU AI Act, India's DPDP, sector regulations — controls mapped per use case.
Incident response
Ready triage, communication, and remediation playbooks that keep model behaviour on track.
Four-step embedding
Frame
Risk-classify each AI use case against your enterprise risk taxonomy.
Design
Controls per risk tier — proportionate and genuinely effective.
Embed
Controls baked into MLOps pipelines and the AI delivery lifecycle.
Evidence
Continuous evidence collection ready for internal and external audit.
Related sub-services
Talk to us about AI governance
Tell us about the AI you have shipped (or want to ship). We will return with a risk and controls plan.