Our first public release of Divinci AI after extensive private beta testing. This release includes all core functionality that allows users to create custom AI solutions.

• Custom AI model creation with no-code interface
• Advanced RAG (Retrieval-Augmented Generation) capabilities
• Document processing and knowledge extraction
• Vector embedding optimization
• API access for enterprise integrations
• Quality assurance tooling for LLMs
• Release cycle management for AI projects

Final pre-release version with completed feature set and significant improvements based on beta user feedback.

• Added enterprise-grade security features and compliance certifications
• Implemented advanced analytics dashboard for tracking AI model performance
• Improved documentation and added comprehensive tutorial system
• Enhanced user interface with accessibility improvements
• Optimized backend performance for faster model training and response times

Major update to our beta platform with expanded features and significant improvements.

• Added support for multi-modal AI models (text, image, audio)
• Implemented fine-tuning capabilities for specialized domains
• Enhanced RAG system with improved context handling and relevance scoring
• Fixed critical issues with document processing for complex file formats
• Added version control system for AI models
• Improved collaboration features for team environments

Stability and security update focusing on core system reliability.

• Fixed memory leak issues in the document processing pipeline
• Resolved authentication issues for enterprise SSO integrations
• Patched security vulnerabilities in API endpoints
• Improved error handling and reporting throughout the system
• Enhanced system logging for better diagnostics

Initial closed beta release of the Divinci AI platform to selected partners and early adopters.

• Core platform functionality released for testing
• Basic RAG capabilities for document processing
• Initial API endpoints for integration testing
• Fundamental user interface for AI model configuration
• Limited dataset support for proof-of-concept deployments