Azure Open AI – What to build first?

Introduction

Azure OpenAI is a powerful tool that can be used to automate processes, extract insights from data, and improve customer satisfaction across a variety of industry verticals. With Azure OpenAI, businesses can create chatbots, analyze customer interactions, detect patterns, generate descriptions, manage store scheduling, translate documents, and automate route and reduce resolution time of helpdesk tickets. Additionally, Azure OpenAI can be used to generate image models for advertisements, extract key information from call logs, suggest long item descriptions, and use intent classification, entity extraction, and sentiment analysis.

Purpose

The purpose of this document is to provide an overview of the similarities that exist across various industry sectors. It is important to understand these similarities as they can serve as a useful starting point when creating an Azure Open AI offering. The following sections will outline the commonalities observed in different industries and provide recommendations based on these findings.

Findings

The commonalities between the use cases across the different industry verticals are the use of Azure OpenAI to automate processes, extract insights from data, and improve customer satisfaction. The use of Azure OpenAI can be used to create chatbots, analyze customer interactions, detect patterns, generate descriptions, manage store scheduling, translate documents, and automate route and reduce resolution time of helpdesk tickets. Additionally, Azure OpenAI can be used to generate image models for advertisements, extract key information from call logs, suggest long item descriptions, and use intent classification, entity extraction, and sentiment analysis.

Suggestions

Azure Open AI Chatbot

The first generic use-case to solve would be to use Azure OpenAI to automate customer service processes. This could include using Azure OpenAI to create a chatbot that can assist customers with common questions and tasks. Additionally, Azure OpenAI could be used to analyze customer interactions and detect patterns that may indicate fraudulent activity. This could help to improve customer satisfaction and reduce the need for manual customer service processes.

A repeatable solution that could be marketed would be to use Azure OpenAI to create a customer service chatbot that can assist customers with common questions and tasks. This chatbot could be customized to the specific needs of the customer and could be used to improve customer satisfaction and reduce the need for manual customer service processes. Additionally, the chatbot could be used to detect patterns that may indicate fraudulent activity, helping to improve security and reduce the risk of fraud.

Semantic Search

One of the most powerful features of Azure Open AI is its semantic search capabilities. Semantic search is a type of search that uses natural language processing to understand the meaning of a query and return more relevant results. With Azure Open AI, developers can create applications that can understand the intent of a user’s query and return more accurate results. Semantic search can be incredibly useful across different industry verticals, as it allows for more accurate and efficient search results, for example:

Healthcare: Semantic search can be used to quickly and accurately search through medical records and research papers to find relevant information. It can also be used to identify potential drug interactions and to provide personalized medical advice.
Retail: Semantic search can be used to quickly and accurately search through product catalogs and customer reviews to find the best products for a given customer. It can also be used to identify related products and to provide personalized product recommendations.
Education: Semantic search can be used to quickly and accurately search through educational materials and research papers to find relevant information. It can also be used to identify potential learning opportunities and to provide personalized learning advice.
Financial Services: Semantic search can be used to quickly and accurately search through financial records and research papers to find relevant information. It can also be used to identify potential investment opportunities and to provide personalized financial advice.

A repeatable solution that could be marketed would be to use Azure OpenAI to create the basis for a sematic search solution to allow customers to query and return more relevant results based on their internal documentation etc.

Building

If you are looking to create a proof-of-concept (PoC) version of the above suggestion, the following links can provide you with the necessary resources to get started.