AI MODEL INVENTORY
See every AI model in your organization. Centralized registry with comprehensive metadata, compliance tracking, risk classification, and automated discovery.
The Shadow AI Problem
Most organizations don't know how many AI models they have, where they're deployed, or which regulations apply.
- ×No central visibility into AI models
- ×"Shadow AI" deployed without approval
- ×Compliance blind spots and regulatory risk
- ×Manual spreadsheets outdated immediately
- ×Can't track model lifecycle or ownership
- Complete visibility across all AI models
- Automated discovery eliminates shadow AI
- Track compliance status for every model
- Real-time sync keeps inventory current
- Full lifecycle and ownership tracking
How It Works
Create a comprehensive registry of all AI models with detailed metadata, compliance status, risk classification, and lifecycle tracking. Auto-discovery scans cloud platforms to detect models automatically, while advanced filtering lets you find exactly what you need in seconds.
Model Inventory Workflow
From discovery to governance—a complete model lifecycle management process.
Register Models
Add models manually or auto-discover from cloud platforms
Document Details
Capture metadata, purpose, risk level, and compliance requirements
Track Lifecycle
Monitor status from development to production to deprecation
Monitor Compliance
Link to audits, tests, violations, and risk assessments
Generate Insights
View portfolio analytics, risk distribution, and compliance status
Comprehensive Features
Everything you need to manage and govern your AI model portfolio.
What You Can Track
Capture every detail about your AI models for complete governance visibility.
- Model name, version, and unique identifier
- Business purpose and use case description
- Model type (classification, regression, NLP, etc.)
- Training data sources and characteristics
- Performance metrics (accuracy, latency, throughput)
- Deployment environment and integration details
- Model artifacts and documentation links
- Applicable regulatory frameworks (GDPR, EU AI Act, etc.)
- Compliance status and score
- Last audit date and next review date
- Identified violations and remediation plans
- Risk assessment results
- Fairness and bias test outcomes
- Assign model owners and responsible teams
- Track who has access and permissions
- Collaboration workspace integration
- Notification and alert configuration
- Change history and version control
- Model portfolio dashboard
- Risk distribution visualization
- Compliance status overview
- Deployment environment breakdown
- Trend analysis and insights
- Export capabilities for audits
Real Success Stories
See how organizations achieved complete AI visibility and eliminated shadow AI.
Challenge:
Bank had 200+ AI models across 15 departments—no central visibility, regulators demanded inventory
Solution:
Deployed AI Model Inventory with automated discovery across AWS SageMaker and Azure ML
Result:
Discovered 73 previously unknown models, achieved 100% inventory coverage, passed regulatory audit
Challenge:
Multiple clinical AI models in production, no tracking of HIPAA compliance status or last audit dates
Solution:
Created model registry with compliance framework tracking and automated audit reminders
Result:
Reduced compliance preparation time from 4 weeks to 3 days, zero missed audit deadlines
Challenge:
Rapid AI experimentation created 'shadow models' in production—engineering didn't know what was deployed
Solution:
Implemented inventory with risk classification and mandatory registration for deployment
Result:
Eliminated shadow AI, classified all models by risk, reduced security incidents by 85%
Translate