Cyanite.ai

What is Cyanite.ai?

Cyanite.ai is a innovative AI company that develops technology for analyzing and understanding music through machine learning models. Its mission is to make vast music catalogs searchable and accessible by automatically extracting detailed metadata such as genres, moods, instruments, and vocal characteristics. This helps solve challenges in the music industry like manual tagging and inefficient search, enabling faster and more accurate music discovery for labels, libraries, and streaming services. Users can integrate Cyanite's API to process audio files in real-time or in bulk, providing actionable insights that enhance recommendation systems and content management. Overall, it serves music professionals by bridging the gap between raw audio data and meaningful, AI-powered applications.

Cyanite.ai's Core Features

• AI-powered music tagging automatically detects and assigns genres, subgenres, moods, instruments, and energy levels to tracks, saving time on manual cataloging.

• Similarity search functionality identifies tracks that musically match a reference song based on attributes like tempo, key, and structure, aiding in playlist creation and recommendations.

• Keyword-to-music search allows users to query descriptive terms and receive matching tracks, simplifying content discovery for creative projects.

• Voice analysis extracts vocal traits such as gender, type, and similarity to other voices, enhancing metadata for vocal-focused music applications.

• Bulk processing enables efficient analysis of large music libraries, providing scalable solutions for enterprises managing extensive catalogs.

• API integration offers seamless incorporation into existing platforms, allowing developers to build custom music intelligence features.

• High-accuracy models, trained on diverse datasets, ensure reliable results across various music styles and languages.

• Real-time analysis processes tracks in seconds, supporting dynamic applications like live music recommendations.

• Customizable metadata extraction lets users focus on specific attributes relevant to their needs, improving workflow efficiency.

• Visualization tools provide graphical representations of music features, helping users understand and utilize analysis results effectively.