SONOTELLER.AI

AI music analysis including song lyrics summarization and musical features

General Information
Company Name
SONOTELLER.AI
Founded Year
2023
Location (Offices)
Spain +1
Founders / Decision Makers
Number of Employees
1
Industries
AI, Music, SaaS
Funding Stage
-
Social Media

SONOTELLER.AI - Company Profile

SONOTELLER.AI is an innovative startup based in Spain that has been making waves in the music and SaaS industries since its founding in 2023. The company's slogan, "AI music analysis including song lyrics summarization and musical features," encapsulates its core offering. SONOTELLER is an experimental AI engine designed to "listen" to music files, providing in-depth insights into song lyrics and musical properties. This includes comprehensive song summaries, language recognition, explicit content flagging, genres and subgenres classification, main instruments used, and moods, among other features. The significance of SONOTELLER's technology lies in its capacity to empower music enthusiasts and industry professionals in managing their music collections and data. It facilitates a better understanding and organization of music across various digital service providers, enabling improved search accuracy, playlist generation, recommendations, autotagging, and audience profiling. The potential application of SONOTELLER's capabilities across the music industry is vast, offering solutions for discovery, organization, and curation. As of now, SONOTELLER has not disclosed its latest investment details, including the amount and the investors involved. However, the startup's focus on leveraging AI for music analysis and organization presents promising opportunities for collaboration and growth within the music and technology sectors. With its innovative approach and potential for disrupting the music industry, SONOTELLER.AI is a venture that investors in the music and AI sectors should keep a close eye on.

Taxonomy: AI music analysis, lyrics summarization, musical features, experimental AI engine, music organization, comprehensive song summary, language recognition, explicit content flagging, music genres and subgenres, instrument recognition, mood analysis, DSP integration, audience profiling, recommendation engine

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