Metadata makes today’s web work. Descriptive data provides the foundation for discovery, recommendation, and personalization — almost everything that we rely on the internet to help us with. But today, management believes there is no way to apply accurate metadata to visual media quickly and easily, at web scale. In a world where we share 1.8 billion photos and 432,000 hours of YouTube video every day, this is a problem.
Management believes that Tagasauris has reinvented metadata for visual media. Today, we solve the metadata problem for major content creators like Disney, ABC, AOL, Trunk Archive and Magnum Photos. Our proprietary (and patent-pending) platform focuses on three key areas:
We combine the efforts of humans and computers to apply networked metadata to visual media, at web scale. By applying metadata, we make a piece of visual media “content aware” — we teach a computer what the content of that image or video is.
We use the principles of linked open data and graph theory to store metadata in a semantic database. By doing so, we take our content aware media and we make it “relationship aware” — we teach a computer not only what’s in an image or video, but also how that content relates to the rest of the world.
We integrate our human assisted computing platform with our semantic database to create an evergreen knowledge graph that’s continuously learning and keeping our networked metadata up-to-date.
We have applied our technology to millions of images, resulting in: improved discoverability and increases in traffic, engagement, and sales for our clients. In 2014, we partnered with Disney and ABC to expand this capability to video content. This year we are looking to grow our client base to include a variety of other broadcasters, content creators, publishers, media and creative companies.
In 2010, on the heels of a successful collaboration with the legendary photography cooperative, Magnum Photos, I began thinking about the possibility of teaching computers to do things with media on the Web. I believe that visual content is the currency of tomorrow's Web, that the shift from hypertext to hypermedia is both inevitable and exciting and, that once computers can understand visual media, a new generation of applications for discovery and visual-first learning will be enabled. Today, these beliefs drive Tagasauris.
We've spent the last four years developing a computational approach that allows us to backfill the so called "semantic gap" with a layer of structured, contextual, relationship-aware data. This data is persisted in a knowledge base we call mediaGraph. mediaGraph has the potential to interlink the currently impoverished, disparate and siloed descriptions of media across the Web and we believe it can power a new breed of knowledge-centric applications in the world of online multimedia.
Frequently Asked Questions
When you complete your investment on SeedInvest, your money will be transferred to an escrow account where an independent escrow agent will watch over your investment until it is accepted by Tagasauris. Once Tagasauris accepts your investment, and certain regulatory procedures are completed, your money will be transferred from the escrow account to Tagasauris in exchange for your shares. At that point, you will be a proud owner in Tagasauris.
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