Predict future actions: 

Ever wanted to predict what will happen, and when? You better use Time Series Processing and Natural Language Processing techniques to predict what events will happen in the future from now. Using deep learning and automatic hyperparameter tuning such as AutoML, it's possible to predict the future. 

Using a transaction history of, say, a coffee shop, we can predict the next product item purchased on a per-client or per-machine basis, and in how much time the consumer would purchase this product given his purchase history. Repair events and all sorts of related events can be predicted and fed into the algorithm as well.

 

Technical Specifications:

Input Data: 

For instance, those events could be related to items to predict as such: 

• Transactions (sales forecast of product items)
• Repairs (predictive maintenance of repair items)
• Clicks in your app (user behavior modeling of action items)

 Those make 4D nested objects of dimension shaped as follow:

[stores, consumers, events, items with metadata]

Output Data: 

Given the event histories as inputs, our algorithm predict, for each possible item in your item set (e.g. products, repair codes, other action types), we predict two variables: 

1. The probability of this item to occur in the future
2. In how much time from now (time delta) in which the event would occur if, it was to occur as pre the prediction at point 1 just above.

 Those make 4D nested objects of dimension shaped as follow:

[stores, consumers, item probability and time delta]

 

Summary: With our solution, you can predict WHICH thing (or WHO) will do WHAT and WHEN.

 

STRUCTURE A B2B DEAL: