iTunes has been offering personalized recommendations within the iTunes application for quite sometime and I have found them to be very accurate and helpful. I have often discovered new songs that I like within the recommendations and downloading them quickly for instant gratification. iTunes has started to role out syndication of personalized music data as My iTunes Widgets, making it easy to share your music interests.
One Llama, a product of six employee Champaign, Illinois-based startup One Llama Media, leverages audio analysis, search and discovery systems to offer a place for music lovers to discover, listen, share and buy new music. Though in the music discovery category, One Llama differs from Last.fm, Pandora and MyStrands by focusing more on search result technology rather than community aspects of music discovery.
One Llama's users interface design is fun and light. Users can search for new music by song or artist and search results are returned in a flashy cluster experience (shown in the screen-shot below) that reminds me of Visual Thesaurus or Quintura. Users can create playlists on their own or One Llama will create a playlist with recommended songs that are similar to a song or songs you have identified. One Llama created a quick list of recommended songs based off of one song I liked. I was then given the option to share, save or buy these tracks or the playlist. I have shared the list below as an embeddable widget but you can also share it directly to Facebook.
If you like a song you can purchase is on iTunes or Amazon. One Llama also offers an iTunes plug-in which links the web to your desktop music making it even easier to find and purchase the songs you just discovered on One Llama.
In talking with Director of Product Development, Amit Sudharshan, a recent graduate of University of Illinois at Champaign-Urbana, he explained that:
"One Llama believes finding music should be a 'fun' experience that people should be able to discover, enjoy and share."
As a music lover myself, I would have to agree. Currently, One Llama uses collaborative filtering to offer up song and playlist recommendations but Amit mentioned that audio signal extraction technology is coming very soon. This will enable One Llama to offer music search technology which uses collaborative filtering to recommend songs that people usually play together as well as signal extraction technology to recommend songs that sound alike. One Llama recently partnered with EMI and APM to power their search and find songs that "sound like" other songs within the APM library.
Sticking with it's 'fun' mission, One Llama shows its lighter side by allowing users the ability to personalize their llama avatar. My llama avatar is shown to the right.
Bottom-line:One Llama offers an innovative music search and discovery technology that is fun and easy to use. I had fun using One Llama and I think you will too.
Startup Mixology: Tech Cocktail's Guide To Building, Growing & Celebrating Startup Success by Frank Gruber