Governance is not paperwork produced for an audit. It is the set of controls that decide whether a model is allowed to affect a real decision at all.
Nine gates before production
Every model passes the same approval sequence before it can affect a customer or a regulated outcome. The gates are the framework your board and regulators review.
Problem & risk framing
Define the decision, its risk tier, and the regulatory obligations it touches.
Data governance
Lineage, consent, and residency of training and inference data verified.
Bias & fairness
Protected-attribute analysis and fairness metrics, documented.
Explainability
SHAP / LIME explanations and a model card produced for the model.
Security & privacy
Threat surface, PII handling, and access boundaries reviewed.
Performance validation
Edge-case and benchmark results signed off against targets.
Human-oversight design
Checkpoints, confidence thresholds, and escalation paths defined.
Approval sign-off
An accountable owner approves the model against the full gate record.
Monitoring & incident plan
Drift thresholds, alert routing, and incident SLAs in place.
Checkbox compliance vs. governance-by-design
Governance added at the end slows delivery and rarely survives scrutiny. Designed in, it does neither.
Built to be trusted in production
Governance is part of the delivery method, not a layer added after launch.
AI cannot act autonomously on high-risk decisions
Human review is mandatory on exception-flagged and high-risk model decisions — a hard rule, not a setting.
Nine gates before production
Every model passes a defined approval process before it can affect a customer or a regulated outcome.
Designed for regulator review
The framework is documented for board and regulator scrutiny from day one — not assembled reactively for an audit.
The delivery timeline, sized by duration
Four phases from maturity assessment to ongoing monitoring — sized by their stated duration.
Segment width follows each phase's stated duration range.
What every governance engagement guarantees
100%
Human review coverage on all exception-flagged model decisions
9-gate
Mandatory approval process for every model entering production
4
Regulatory frameworks mapped to every engagement — DPDPA, RBI, GDPR, EU AI Act
The right engagement profile
Chief Risk Officers
Requiring a structured framework for model risk and autonomous system oversight
Compliance & Legal Teams
Building AI governance to satisfy regulator expectations in BFSI, healthcare, and public sector
CDO / Data Science Leaders
Needing governance infrastructure before scaling AI deployments across the enterprise
Software behind this service
Where this service has the most impact
Questions buyers ask first
Will governance slow our delivery down?
It is designed not to. Governance is embedded into the development process as gates and documentation, so it runs alongside delivery rather than blocking it at the end.
Which regulations do you cover?
DPDPA, RBI AI guidance, GDPR, and the EU AI Act, mapped to your model inventory and sector.
What is the 9-gate process?
A defined sequence of approval checkpoints every model passes before production, covering risk, bias, explainability, and oversight.
Can you audit models we already have in production?
Yes — the maturity assessment covers existing models and returns a gap register with prioritised remediation.
NOT SURE THIS IS YOUR GAP?
The AI Readiness Assessment scores governance design alongside the three other layers a programme depends on, and tells you which one is holding the rest back. About five minutes, nothing is sent anywhere.
Score your readinessBring governance into your AI delivery
Book a 40-minute discovery call to scope a governance maturity assessment for your model estate. No commitment.