Shopping can be a huge pain, especially with annoying sales people. We all have been wasting time looking for the right size or desired colour of the wanted item, and even when the sales person takes a look at the stock, (s)he will often come back, telling you they are out of stock. That is a huge waste of time and needs to be improved.

What it does

Vendio is your very own sales assistant. No more uninformed sales people, no more waiting for customers, and no more unwanted pressure for purchase. But that's not everything. Vendio will also give you recommendations, based on a combination of informations about trending items, your shopping history and your personal style and boost sales.

After all, it will also safe the retail business lots of money and set enough work force free, to compensate for Japan’s declining population.

How I built it

Vendio was built using IBM Watson, python, web dev, cyclone, javascript, etc.

Challenges I ran into

Mobilizing Pepper.

Accomplishments that I'm proud of

QR code reader to identify unique customers and visual recognition model to identify style preference using machine learning

What I learned

What's next for Project Vendio

Next steps for Vendio are:

  1. Even more data driven recommendations More personalisations, using our style recognition algorithm Emotional response to learn personal preferences Facebook API —> bring in external data to help our algorithm to learn more about customers

  2. Customer Experience Pepper scans the bar code of the item you are holding, to make inventory checks more efficient Quick check-out avoiding unpleasant waiting time Adding conversation capability

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