> ## Documentation Index > Fetch the complete documentation index at: https://docs.regpilot.dev/llms.txt > Use this file to discover all available pages before exploring further. # AI Models Registry > Centralized registry for AI models with risk classification ## AI Models Registry The Models Registry is your centralized hub for managing all AI models used in your applications, including risk classification, compliance status, and performance monitoring. ## Why Register Models? Required for high-risk AI systems under EU AI Act Automatically classify models by risk level Maintain technical documentation for each model Track model performance and compliance over time ## Risk Classifications Models are classified according to EU AI Act risk levels: **Prohibited** - Cannot be deployed * Social scoring systems * Subliminal manipulation * Exploitation of vulnerabilities * Real-time biometric identification (with exceptions) **Strict requirements** - Full compliance needed * Employment decisions * Credit scoring * Educational admissions * Law enforcement * Critical infrastructure **Transparency obligations** - Disclosure required * Chatbots * Emotion recognition * Biometric categorization * Deepfake generation **No specific obligations** * Spam filters * Video game AI * Inventory management ## Registering a Model ```typescript theme={null} const model = await regpilot.models.register({ name: "Customer Support Classifier", version: "1.0.0", provider: "openai", model_id: "gpt-4-turbo", description: "Classifies customer support tickets" }); ``` Select the appropriate risk level based on intended use: ```typescript theme={null} await regpilot.models.update(model.id, { risk_level: "limited", intended_purpose: "Customer support automation", target_users: "Customer service representatives" }); ``` Upload required documentation: * System architecture * Training data description * Performance metrics * Risk assessment Configure compliance monitoring: ```typescript theme={null} await regpilot.models.setCompliance(model.id, { frameworks: ["eu_ai_act", "gdpr"], monitoring_enabled: true, governor_enabled: true }); ``` ## Model Information Each registered model includes: ### Basic Details * Name and version * Provider and model ID * Description and purpose * Deployment environment ### Risk Assessment * Risk classification * Intended purpose * Target user groups * Potential risks identified ### Technical Documentation * Model architecture * Training data sources * Performance metrics * Validation results * Bias testing results ### Compliance Status * Applicable frameworks * Compliance score * Active violations * Last assessment date ## Managing Models ### Update Model ```typescript theme={null} await regpilot.models.update("model_123", { version: "1.1.0", status: "production", performance_metrics: { accuracy: 0.94, f1_score: 0.92, latency_p95: 250 } }); ``` ### Archive Model ```typescript theme={null} await regpilot.models.archive("model_123", { reason: "Replaced by v2.0", replacement_model_id: "model_456" }); ``` ### Generate Documentation ```typescript theme={null} const docs = await regpilot.models.generateDocs("model_123", { format: "pdf", include_sections: [ "technical_specs", "risk_assessment", "compliance_status", "performance_metrics" ] }); ``` ## Model Monitoring Continuous monitoring includes: * **Performance Tracking**: Accuracy, latency, error rates * **Compliance Validation**: Ongoing EU AI Act checks * **Bias Detection**: Regular fairness assessments * **Usage Analytics**: Request volumes and patterns * **Incident Tracking**: Errors and violations ## Compliance Requirements For **high-risk models**, you must maintain: * Detailed system description * Development and testing procedures * Risk management documentation * Data governance records * Identified risks and mitigations * Residual risk evaluation * Testing and validation results * Ongoing monitoring procedures * Training data description * Data quality metrics * Bias assessments * Data provenance records * Oversight measures * Stop/override capabilities * Human-in-the-loop procedures * Responsibility assignment ## Best Practices Register models during development, not just at deployment Track all model versions with detailed change logs Keep documentation and compliance status current Enable ongoing performance and compliance monitoring Record all updates, incidents, and modifications ## Next Steps Learn about EU AI Act risk levels Technical documentation guide Models API documentation Enable Governor validation