Intellicase
Bot (GPT)

Problem Statement

Sales teams and website visitors often struggle to find relevant Topcoder case studies using traditional search methods. Keyword-based searches often miss important contextual information, leading to a suboptimal user experience. A conversational chatbot powered by GPT can address this challenge by inferring the intent behind user inquiries and providing personalized, nuanced responses.

Objective

The goal of this project is to develop a GPT-powered conversational chatbot that can:

• Effectively search and retrieve relevant Topcoder case studies based on user inquiries.
• Infer the nuances of user inquiries, even when keywords don’t match exactly.
• Provide insightful responses that go beyond mere keyword matching, including personalized recommendations and contextual insights.
• Do so, by finding and evaluating data where it exists, without changing or moving it, or requiring new catalogs.
• For full details on how the chatbot will be evaluated, register for the challenge.

Success Criteria

The chatbot will be considered a success if it can:

• Accurately identify relevant case studies for a variety of user inquiries.
• Provide nuanced responses that demonstrate an accurate inference of the user’s intent.
• Effectively engage in conversations with sales and website visitors, providing a positive user experience.

AI Technology Stack

Offline GPT (Generative Pretrained Transformer) Model