Govern the AI you build and buy - model inventory, risk and bias testing, responsible-AI policy and ISO 42001 readiness - so innovation stays accountable.
Teams are shipping models and adopting AI vendors with no inventory, no risk view and no policy. Regulators and customers are now asking who owns the risk. Governance shouldn't block AI - it should let you deploy it with confidence and a paper trail.
Each capability plugs into the same evidence repository and client portal.
Discover and catalogue every model and AI vendor in use across the business.
Rate each use-case for risk, impact and regulatory exposure.
Stand up an AI Management System aligned to the standard.
Test models for bias, drift and fairness before and after deployment.
Practical policy and acceptable-use guardrails your teams will follow.
Privacy impact assessments for AI processing personal data.
Assess third-party AI tools for security, privacy and IP risk.
Ongoing oversight of model performance, drift and incidents.
No black box. You see exactly what we do, when, and what evidence it produces.
Start a pilotFind every model and AI service - built, bought or shadow.
Risk-rate each use-case and flag the high-impact ones.
Stand up policy, an AIMS and an approval workflow for new AI.
Run bias, fairness and security testing pre- and post-deployment.
Continuously watch for drift, incidents and new obligations.
Four accountable workstreams connect discovery, implementation and evidence without unnecessary complexity.
Defined scope, accountable ownership and documented evidence.
Defined scope, accountable ownership and documented evidence.
Defined scope, accountable ownership and documented evidence.
Defined scope, accountable ownership and documented evidence.
Decision-ready documentation, operational assets and evidence delivered through the client portal.