Trigger-Based Retraining

• Performance degradation detection triggers
• Environmental drift detection (lighting, scene changes)
• Scheduled & event-driven retraining pipelines
• Data volume threshold triggers
• Manual trigger with one-click retraining

Model Registry

• Centralized model artifact storage & versioning
• Model metadata (architecture, dataset, metrics)
• Lineage tracking from data to deployment
• Secure model artifact signing & verification
• Model comparison & promotion workflows

Staging → Production Workflow

• Multi-stage deployment pipeline (dev → staging → prod)
• Canary deployments with gradual traffic shifting
• A/B testing between model versions
• Approval gates with stakeholder sign-off
• Automated smoke tests at each stage

Fast Rollback Mechanism

• One-click rollback to any previous model version
• Automatic rollback on performance threshold breach
• Zero-downtime model swapping
• Rollback audit trail & notifications
• Fallback model configuration per deployment