Changelog
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2.0
Version 2.0April 12, 2025Major
New Features
- Introduced visual workflow builder for creating complex AI pipelines without code
- Added support for custom model hosting with auto-scaling capabilities
- Implemented real-time analytics dashboard with customizable metrics
- Added A/B testing framework for model deployment and evaluation
- Introduced model versioning system with automatic rollback options
Improvements
- Redesigned user interface for improved usability and accessibility
- Optimized model deployment process, reducing average deployment time by 40%
- Enhanced security features with SOC 2 Type II compliance
- Improved API documentation with interactive examples
Bug Fixes
- Fixed issue with model monitoring alerts not sending notifications
- Resolved authentication token expiration handling
- Fixed data visualization rendering in Firefox browsers
1.5
Version 1.5March 15, 2025Minor
New Features
- Added integration with GitHub for CI/CD workflows
- Implemented custom model metrics for performance monitoring
- Added support for team collaboration with role-based access control
Improvements
- Enhanced model serving infrastructure for better performance
- Improved error handling and logging for troubleshooting
- Updated documentation with more examples and tutorials
Bug Fixes
- Fixed pagination in model list view
- Resolved issue with webhook delivery on certain network configurations
- Fixed inconsistent dark mode styling
1.4
Version 1.4February 28, 2025Patch
New Features
- Added support for custom Python dependencies in model environments
- Implemented scheduled model retraining
Improvements
- Optimized model loading time for faster inference
- Enhanced user authentication system
- Improved dashboard performance for projects with many models
Bug Fixes
- Fixed model export functionality for certain model types
- Resolved UI rendering issues in Safari browsers
1.0
Version 1.0January 10, 2025Major
Initial Release
- Launched Simplify AI platform with no-code AI model deployment
- Introduced visual interface for AI model management
- Added support for common ML frameworks: TensorFlow, PyTorch, and scikit-learn
- Implemented basic monitoring and logging for deployed models
- Released REST API for programmatic access to platform features
- Added user management and authentication system
- Implemented essential security features for data protection