INTRODUCTION

Overview

We will be designing an application that leverages multiple Watson Airservices (Discovery, Assistant, Cloud function, and Node Red). By the end of the project, we’ll learn best practices of combining Watson services, and how they can be used to build interactive information retrieval systems with

Discovery + Assistant.

• Project Requirements: Python, IBM Cloud, IBM Watson
• Functional Requirements: IBM Cloud
• Technical Requirements: AI, ML, WATSON AI, PYTHON
• Software Requirements: Watson assistant, Watson

Scope of Work

• Create a customer care dialog skill in Watson Assistant
• Use Smart Document Understanding to build an enhanced Watson Discovery collection
• Create an IBM Cloud Functions web action that allows Watson Assistant to post queries to Watson Discovery

Proposed solution

For the above problem, we are able to put a virtual agent in the chatbot so it can understand the queries that are posted by customers. The virtual agent should train from some insight records-based company background so it can answer queries supported by the merchandise or associated with the company. In other words, some styles of manual will be accustomed to training the bot using AI. Here I’m using Watson Discovery as a tool for implementing AI and getting trained by the owner’s manual.

THEORETICAL ANALYSIS

Block/Flow Diagram

Hardware / Software Designing

1. Create IBM Cloud services
2. Configure Watson Discovery
3. Create IBM Cloud Functions action
4. Configure Watson Assistant
5. Create flow and configure the node
6. Deploy and run Node-Red app

EXPERIMENTAL INVESTIGATIONS

Create IBM Cloud services

Create the following services:

• Watson Discovery
• Watson Assistant
• IBM cloud function
• Node-Red

Advantages

• Companies can deploy chatbots to rectify simple and general human queries.
• Reduces manpower

• Cost efficient
• No need to divert calls to customer agents and customer agents can look at other

Disadvantages:

• Sometimes chatbots can mislead customers
• Giving the same answer for different sentiments.

• Sometimes cannot connect to customer sentiments and intentions

APPLICATIONS

• It can deploy in popular social media applications like Facebook, slack, and telegram.
• A chatbot can deploy any website to clarify basic doubts of viewer

CONCLUSION

By doing the above procedure and all we successfully created an Intelligent help desk smart chatbot using Watson assistant, Watson discovery,

Node-RED and cloud functions.

FUTURE SCOPE

We can include Watson studio text-to-speech and speech-to-text services to access the chatbot hands-free. This is one of the future scopes of this project.