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Conversational AI Chatbot

 

 

Conversational AI Chatbot

Overview

The client, an independent software vendor, wanted to automate the interaction and information-sharing process with the end user whenever a query was generated. They wanted to replace it with AI-powered chatbots that could chime in and remove the dependency on a human counterpart.

Problem Statement and Challenges

The client incurred high costs to maintain a division for responding to queries generated by the end users. Although connecting with a representative for complex questions makes sense, a better and more optimised solution was required for simple queries or just common faq.

Additionally, due to human factor involvement, the client had inconsistencies in the systems, such as missed queries, delayed response time, and much more.


Solution

We used Microsoft Azure Bot Service, a platform to build enterprise-grade conversational AI bots, to develop a chatbot that uses NLP or Natural Language Processing and mimics a conversation very closely to how a human would. Moreover, it was integrated with the Instant Messaging platforms used by the client at the time of implementation, such as MS teams, Slack, and more.

On top of all this, we also migrated the chatbot data from MongoDB to CosmoDB for faster and optimised processing while following all the compliances. Lastly, we topped it off by implementing Context to Call, our in-house 'click to call' application for directly making calls, messages, and emails over the web. This helped when the end-user wanted to connect with a human instead of a bot.

  • Microsoft Azure Bot Services
  • Natural Language Processing
  • Integration With Instant Messengers
  • Migration From MongoDB to CosmoDB
  • Integration of Context to Call
  • Constant Evolution Via Artificial Intelligence
  • Compliance Management
  • Website Based Implementation

Results and Success Criteria

Using Artificial intelligence, the chatbot not only answers the queries effectively but also learns to predict the flow of conversation for a future use case. Moreover, we implemented the chatbot for a web-based service, which can be easily migrated to IOS and Android if needed.