AI Inventory & Intake
Create a consistent way to register AI use cases, systems, models, agents, owners, purpose, data, vendors, and deployment context.
Scale AI With Confidence.
We help organizations establish the governance, accountability, controls, and evidence required to manage AI from idea through production and ongoing operation.
Govern AI across the lifecycle
AI governance should begin before development and continue after deployment. We help organizations create a lifecycle that identifies accountable owners, classifies risk, defines control requirements, validates data and models, manages approvals, monitors operation, and triggers recertification when material changes occur.
- Intake
- Risk Tier
- Data / Model Review
- Build
- Validate
- Approve
- Monitor
Risk Classification
Tier AI use cases based on business impact, autonomy, data sensitivity, regulatory exposure, decision consequence, and other risk factors.
Lifecycle Controls
Define checkpoints for data readiness, architecture, security, privacy, testing, validation, human oversight, approvals, deployment, and monitoring.
Responsible AI
Translate principles such as fairness, transparency, accountability, privacy, security, and human oversight into practical requirements and evidence.
Model & Agent Governance
Establish expectations for models, prompts, tools, permissions, agent autonomy, evaluation, versioning, and changes.
Third-Party AI Risk
Assess vendor AI capabilities, data handling, controls, contract requirements, model behavior, and ongoing monitoring responsibilities.
AI Monitoring
Track performance, quality, safety, incidents, drift, adoption, cost, exceptions, and changes in the operating environment.
Evidence & Recertification
Retain decisions and evidence and define when material changes, time-based reviews, or incidents require renewed approval.
A governance model that supports innovation
The objective is not to create a single heavy process for every AI use case. We use risk-based governance so lower-risk applications can move through a proportionate path while higher-risk use cases receive the additional review, evidence, testing, and oversight appropriate to their impact.
Build the governance foundation for enterprise AI.
We can help you define the lifecycle, controls, roles, evidence, and technology needed to govern AI as adoption expands.