SONOTELLER is an AI-powered music analysis tool designed to provide comprehensive insights into songs by examining both lyrics and musical components. By 'listening' to music files, SONOTELLER generates detailed summaries that include genre classification, mood identification, instrumentation, tempo (BPM), key, and more. This enables users to gain a deeper understanding of their music and enhances the discoverability of songs across various platforms. Key Features and Functionality: - Lyrics Analysis: Provides summaries, identifies themes, detects explicit content, and recognizes language. - Music Analysis: Determines genres, subgenres, moods, instruments, BPM, key, and vocal characteristics. - Golden Minute Identification: Highlights the most impactful segment of a song, such as the chorus. - API Integration: Offers dedicated API endpoints for scalable music and lyrics analysis, facilitating seamless integration into catalog management workflows. Primary Value and User Solutions: SONOTELLER simplifies music catalog management by automating the tagging process, making it easier for music professionals to organize and distribute their content. By enriching music descriptors, it enhances music discovery and distribution, ensuring that songs are more accessible and appealing to listeners. This tool is particularly beneficial for music labels, publishers, and content companies aiming to optimize their catalog delivery to digital streaming platforms with DDEX-compliant metadata, including lyrical themes.