Virtual Assistant using NLP

E-commerce Virtual Assistant NLP

The use case here is to build a virtual assistant or chatbot using NLP which will help the e-commerce site to sell products and increase customer satisfaction.



  • Our client is from the e-commerce services who are majorly looking for a solution for their e-commerce business. Their solution involves advanced usage of AWS along with Natural Language Processing to make sure that the business is profitable.
  • The client was specific about their requirement on accurate detection of user’s emotion through voice and text
  • Our team designed and implemented the solution using seven plus technologies which included Natural Language Processing, Machine Learning, Artificial Intelligence, Scala and PyTorch.

Tech Challenge

  • The solution should be able to understand different voices and should be able o understand different languages.
  • The chatbot should be able to generate different emotions and intensity.
  • The system should be able to chat with the user and give accurate responses.
  • The response time of the solution should be very quick.


  • The system is capable enough to get different voices and process through NLP and Text Mining.
  • Different intensity and emotions were captured efficiently using TensorFlow and Scala
  • The solution uses the time tracking algorithm to make sure that response time is accurate
  • The virtual assistant uses reinforcement learning to receive rewards from users

Project Planning

  • 2 Week -Solution Architecture Desgin -Solution Architect

  • 4 Week - Integration, Testing and Deployment

  • 6 Week - Exploratory Data Analysis and Model Building

  • 8 Week - Collection of data and realtime streamlining and development


  • We have developed a solution that is backed with a lot of advanced technologies thus making the solution accurate and fast.
  • The solution is capable of processing large amounts of data coming from different resources.
  • The solution allowed the customers to rate their experience and also all types of voices from different languages can easily be analyzed.

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