Check out our slide deck here!


The hive is everywhere. Everyone has opinions. And anyone could look for advice to everyday questions. In fact, we make an average of 35,000 decisions a day. We’re connecting users all around the world so that any user can solicit opinions from anyone anywhere any time, in real-time. Just hive it on

“Self-expression is everything. But I calibrate how I express myself based on how others respond.” Daniel, 25, Sao Paulo, Brazil.

“I only text a few people, but put out memes on the internet to random people all the time” Megan, 20, Long Island, USA

“I always poll my friends before I decide on an Instagram caption - it helps make sure I get more likes!” Kristin, 24, Berlin, Germany.

What it does

What if you could tap into a readily-available online community & collect suggestions on these everyday decisions in real-time?

And what if we could collect this data for a ML algorithm (fed onto a Messenger Chatbot or a voice assistant, like FB Aloha) that is enabled to make these simple everyday questions for you in a considered, human-centered way?

How I built it

We focussed on one use case: deciding what outfit to wear.

Built two modules:

  1. Sourcing preference data through a fun user-friendly product that was designed using various UX tools and then put together on Wix and using JS.

  2. Developed a ML algorithm that takes this user preference data & predicts preferences for future uploads.

The ML Algorithm was built as follows:

  1. Using Google cloud automated machine learning vision tool to classify clothes.
  2. A recommendation to a product will be assigned based on the popularity in the market, people will answer the question by selecting the recommended item & a percentage voting weight will be assigned to each item
  3. Using the output from stage 1, the selection process will be determined by applying a mathematical model we developed.

Challenges I ran into

-Initial challenges integrating our ML algorithms to the Wix Code since we were using Python. Transferred this over to node.js. -Design issues around the mobile site, which we were able to fix by implementing changes on the mobile version on Wix.

Accomplishments that I'm proud of

-Designing & building something that was usable and, in our opinion, very practical!

-There was a steep learning curve since all the platforms were very new to us. We're very proud of how we were able to pick them up together as a team.

What I learned

-Using Wix Code and integrating it with various back-end systems. -It was our first attempt at building a complex ML algorithm -Working with a very diverse team from all around the world, with a broad range of skills - this was the best thing we could learn!

What's next for

  1. Show prototype to sample of users to collect initial feedback
  2. Test beyond clothing options
  3. Build out results page with demographics info (e.g. a map with where votes are coming in from using
  4. Define the monetization model -charge for app installs -trial & in-app purchase -freemium opportunities -Ripple payment per Q and payment per swipe
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