| Website | the.echonest.com |
| Blog | blog.echonest.com |
| Category | Games, Video and Entertainment |
| Employees | 10 |
| Founded | 6/05 |
| Series A, 9/08 Commonwealth Capital Ventures |
The Echo Nest is a music intelligence company that develops music search, personalization and interactivity applications powered by a Musical Brain. The Musical Brain automatically reads about music and listens to music everywhere on the web. The Musical Brain is accessible to online music services and developers via a series of web-services APIs.
The company’s second application, Recommend, is an application programming interface that helps music services personalize their websites to each visitor’s unique music taste. Any music website – bloggers, social networks, Internet radio or retailers – can easily access the Recommend API to offer users better music discovery tools.
The company was awarded a Phase II SBIR grant from the National Science Foundation in May, 2008. The grant will support The Echo Nest’s continued development of its “Musical Brain,” a large-scale data mining platform that actually reads about music and listens to music everywhere on the internet. The Echo Nest will apply its network and sentiment analysis technology to automatically cluster online communities by music preference and more deeply understand online music sentiment.
The Echo Nest Analyze API is a tool that enriches your software’s understanding of music. It uses a perceptual model of human listening to generate detailed XML descriptions of a song’s structure and musical content to power music applications with a much deeper musical understanding.
| Stage | Live |
| Launch Date | May, 2008 |
The Echo Nest Recommend API powers recommendations by understanding every song, review and news article on your music site. Personalize your site to each user’s unique music taste. Drive page views and increase time-on-site by helping users discover great new music.
The Echo Nest’s Musical Brain combines large-scale web crawling, data mining, language processing and audio analysis to:
Read about music, constantly crawling the web and analyzing the text on millions of web pages (music reviews, artist sites, blog posts) to understand what the entire online world knows about every artist, album and song.
Listen to music, analyzing all of the music on the web to extract musical attributes such as key, tempo, rhythm, harmonic and timbral structures, understanding every song in the same way a musician would describe it (i.e.,“swing groove, tempo = 100 BPM, 4/4 time, key of B Flat, mezzo piano”).
Predicts music trends, synthesizing online behavior to actually predict new music trends.
