VMware Inc.

06/27/2022 | News release | Distributed by Public on 06/27/2022 05:41

All About Chatbot for Business Operations

by: VMware Senior Member of Technical Staff Peter Amal Raj

Introduction

Addressing customer questions and reducing ad hoc queries is a big challenge for any organization. To mitigate this, organizations are filling FAQ pages and some websites with a lot of details. However, the real challenge is that customers usually do not visit web pages or FAQs to get their answers. The solution VMware IT brings to our platform is the emerging "Chatbot for Business Operations." This is designed and built with end customers and business teams in mind, which provides the respective information in real time and reduces ad hoc requests. Furthermore, it saves customers or business users time by providing the relevant information at fingertips.

The challenge

VMware business teams were spending a lot of time retrieving required information as part of daily operations. The various information was hidden across various application pages and the business teams were spending valuable time navigating around this.

Due to this, business operations and decision-making time were being delayed, contrary to our vision of, providing business information to users' fingertips with less effort and in less time.

To fulfil this vision, VMware IT built a chatbot that works with our artificial intelligence (AI) and microservice architecture to ease business operations.

The implementation

This is an interactive-based chatbot that helps business users retrieve their required business data in practically no time at all. The best part about this chatbot is that business users do not need special training to use it. It can be integrated with any UI channel.

  • Improves efficiency and productivity of the business users
  • Single bot with various access levels for various use cases

The Chatbot flow starts with the business user command/request from the UI channel. The user request will be received and passed on to the processing manager. The processing manager will feed the request into the AI system to convert the user request to the machine-understandable format (intents and entities). One of the recommended open-sources AI is "RASA AI"

AI system will send back the intent and entity details back to the processing manager. Based on the values, the processing manager will call the authentication service to validate the user permission. If the authentication is passed, the respective microservice end points will be triggered to get the business data. Once the data is retrieved, based on the UI channel, the UI response will be formatted and displayed back to the business users. See Figure 1.

Figure1: Chatbot architecture

For the Chatbot, role-based authentication system is the right choice as it provides a deep level of control for user authentication.

Some implemented business scenarios

  1. Getting order details with 'Hold'
    1. This feature accesses the important details of the order in the UI. This helps business teams to see the required details and make the right decision.
  2. Getting order holds list for past 10 days
    1. This service provides business users with the details of the orders, which are on hold for the given number of days. This helps business teams take corrective measures based on the results.
  3. Getting contract information
    1. This feature pulls the contract information on the UI, which helps the business team understand the current status of the contract.
  4. Getting a product activation code (PAC) redemption report
    1. This report helps the business team analyze the PAC redemptions.
    1. Currently, no reports PAC redemption reports are available; due to this, business teams spend several hours consolidating the data.

Advantages

  • Real-Time Communication: as the bot directly processes the user request with the real-time services, the response is instantaneous.
  • 24/7 availability and reduce the manual effort of the business users in the information search, which improves the productivity.
  • As the bot has been implemented on microservice technology, implementing any new business scenario will be faster.
  • Provides access to various levels of information and reports based on the users' roles and responsibilities.

What's next?

Currently, the chatbot has been implemented to connect only to the Oracle EBS Order Management System. The upcoming plan is to extend the services to add SAP-related business scenarios.

We're also planning to expand the usage to various business teams, including Sales, that will reduce their workload tickets.

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