MAMIO is an existing digital health start-up that uses image recognition to track medicine intake. At the hackathon we saw potential to partner up with Deutsche Bank and create a new functionality for MAMIO.

What it does

MAMIO expenses extracts text from receipts and combines them with the Accountinsights API to create a split of medical expenses per product. It can then notify the user of how much of their total budget they are spending on a given product.

How I built it

Starting from a Marionette.js framework, we decided to fill it in with Deutsch Bank API users insights data, in correlation with their purchases, on one hand. On another, we are a startup building an image-recognition application that extract relevant info from medicine intake and/or prescriptions and receipts. We therefore decided to match users purchase of medicine with their past history and suggest items.

Challenges I ran into

Processing users data from DB API + recommender algorithm.

Accomplishments that I'm proud of

A end-to-end web app that extract text, and present DB users purchase data in a friendly way

What I learned

Managing time + parse json for data to text

What's next for MAMIO

Text to speech and predictive analyitics.

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