Musical-Agent-Systems offers a modular architecture where each musical agent encapsulates behavior models, event schedulers, and synthesis controllers. Users define agents via configuration files or code, specifying generative algorithms, response triggers, and communication protocols for ensemble coordination. The system supports real-time performance through efficient scheduling, enabling dynamic adaptation to external inputs or other agents' outputs. It includes core modules for pattern generation, machine learning–based style modeling, and MIDI/Open Sound Control (OSC) integration. With extensible plugin support, developers can add custom synthesis engines, analysis tools, or AI models. Ideal for academic research, interactive installations, and live algorithmic performances, the framework bridges computational creativity and practical music-making workflows.

ChopLab automates the process of splitting, isolating, and chopping audio tracks into individual samples using advanced AI technology. Simply upload any song and the AI handles the rest. Users can also generate custom loops or one-shot samples by providing a few descriptive words. The platform includes an extensive library of unique, high-quality AI-generated samples ready to be used in music production. With features like key and BPM detection, Web-MIDI interface, and secure data handling, ChopLab offers a comprehensive solution for modern music creators.