Discovery of Generative AI FAQ Bot

Updated 

Overview

This article will serve as a guide to discovering the requirements for building a Generative AI-powered FAQ Bot.

Use Cases of Generative AI FAQ Bot

Identify your requirements for the FAQ Bot. Depending on your needs, two main use cases can be as follows:

  • Fully FAQ-Based Bot: If your requirements are to have an FAQ Bot powered by Generative AI that answers questions from a pre-defined knowledge base.

  • Journey-Based Conversational Bot: If you need a mix of transactional journeys and answering FAQs, the bot will be designed to not only respond to FAQs but also manage and promote user engagement along specific transactional paths. This can be implemented in two ways:

    • Selecting a bot menu that engages the Generative AI-based bot.

    • Running on the fallback messages.

Languages for Generative AI Bot

  • Languages for Generative AI Bot

  • Determine the number of languages in which the bot is expected to respond. Each language should be treated as a separate workflow, and the build time for each language will be planned accordingly.

Compiling Training Content

Preparing Training Data

  1. Coherent and Logical Flow: Ensure that the training data, whether in text or tabular format, has a coherent and logically flowing language. It should read like a properly written piece of text, making sense, flowing naturally, and easy to understand.

  2. Minimal Columns in Tabular Data: Tabular data with numerous columns may result in lower accuracy due to the structural similarity between entries, which reduces semantic search results. It's advisable to include only necessary data, using as few columns as possible. If using multiple columns in an Excel file, ensure they provide additional information beyond the existing text. For example, adding a column for topics or themes can provide additional context while training.

Testing and User Acceptance Testing (UAT)

Curate a Golden Test Set.

What should be included?

Compilation of user queries along with preferred responses (optional).

Determine the number of user queries to be included in the test set.

Ensure the test set encompasses the breadth of content found in the training data, covering all possible query combinations.

How will this be utilized?

Utilize Golden Test Set to assess the performance of the test.

What's Next?

Get started by building your own Generative AI powered FAQ bot!