We’re giving away 1,500 DJI Tello drones. Enter to win ›
Get the code
View the demo
By Muralidhar Chavan, Manjula Hosurmath | Published October 3, 2018 - Updated October 3, 2018
Artificial IntelligenceKnowledge DiscoveryNatural Language Processing
This code pattern walks you through creating an automated and cognitive method of providing customer support. Using the telecommunications domain as an example, it steps you through various customer support scenarios such as enabling a service, disabling a service, changing a plan, and adding a family member to a plan.
Organizations receive communication daily from their customers through various channels like emails, phone calls, and job applications. For better customer support, it’s important to act on these communications quickly and accurately. However, manually handling the thousands of emails is time consuming and can be error prone. Building an automated, intelligent system to handle customer communication is needed, and this code pattern helps by creating a system that understands the intent and content of emails, determines if the email has all of the required information to process the request, and composes an email asking for missing information.
The code pattern uses natural language processing and understands the intents of the emails, auto-composes responses, and provides a dashboard with a high-level summary of intents and emails. While this code pattern uses a telecom domain, you can apply it to any domain. It uses Watson Knowledge Studio for custom domain natural language processing, Watson Natural Language Understanding to deploy a custom domain model and get entities from emails, Watson Natural Language Classifier to get the intent of an email, a CloudantNoSQL database to store emails and customer data, and Node-RED to integrate with emails.
After completing this pattern, you will know how to:
You can find detailed instructions in the README file. Those steps will explain how to:
November 13, 2018
November 23, 2018
Artificial IntelligenceKnowledge Discovery+
November 26, 2018
Back to top