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04-Jun-2020 00:00

According to a 2014 Kenya demographic and health survey: It was important to us to make sure this youthful population not only gets necessary information on sexual and reproductive health, but also accurate and helpful information — without fear of judgement, when they need it most. We saw this technology as an opportunity — we could be the first to to deliver sexual health education via an app or a chatbot in messaging apps. So far, we have been asked over forty thousand questions from over 4,000 users from all over the world. Our users can ask Sophie free-form questions like: Sexually transmitted infections (STIs) are infections transmitted by having unprotected sex with an infected partner.

With Sophie Bot — we can answer important sexual and reproductive health questions for our users, no matter where they are or what they’re doing. STIs are some of the most common communicable diseases in Kenya, particularly among young people aged 15-24 years.

In this post, we’ll dig into the machine learning and deep learning techniques that power Sophie Bot, as well as Irving’s own journey building an AI startup in Africa. We’re a Kenyan AI startup that answers your questions on sexual health.

Let me give you a bit of background about why we’re building this company.

In the backend, whenever we get a question, we’re using parsing the sentence, and then determining what’s the best response to provide.

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My plan was to monitor new questions and add them to our knowledge base over time. He made the bot classify questions and statements, but it couldn’t do much more about delivering answers — and that was our biggest problem. It was at the time we developed an NLP pipeline to gather even more cool insights on the data we had collected.We then could automatically extract and group topics through topic modeling and a K-means clustering.



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