Model Versioning is the practice of tracking and managing multiple versions of AI models throughout development and deployment. Each version can be tested, compared, rolled back, or audited independently.
Voice AI platforms use Model Versioning to safely deploy model updates, compare performance, support regulatory compliance, and maintain reliable speech recognition and conversational AI services over time.