instantly translates low resource languages, unlocking the
web for the next billion users. The content of the web is not available in the native languages of a billion people. This holds communities back from participating in the web and cuts companies off from accessing these emerging economies.
We combine offline and online data to build parallel corpora to power machine translation for low resource languages. We make this available via an API to local and global companies, allowing them to communicate with customers in these markets.
We have a range of customers, data sharing partners and the largest
datasets in the world for our first two languages.
has scaled international development programs in two countries, co-founded two technology companies and was the product lead for a successful UK government technology application. When he was 17 he cycled 4,500km from Vancouver to Toronto in 30 days and raised $45,000 for cancer research.
Asmelash Teka Hagdu
is finishing his PhD in Applied Machine Learning from Leibniz University Hannover. He indexed and analyzed more than 6 billion tweets and worked on cross-lingual short text matching. He co-founded a startup where he scraped the web to build risk profiles of companies.