The main challenge faced by the SBREAD team in Project Dill was to create custom intelligent chatbots that can be designed for different companies and industries to improve client interaction, speed up the process, mitigate the turn around time and also eliminate the need for dedicated support teams. Additionally, the team had to find a way to train GPT on specific data to ensure that the chatbots respond based on the data provided and not just the internet's decision.
To overcome the challenges, the team at SBREAD decided to train GPT on specific data to give it a preferred bias and personality. The team designed and engineered version 1 of Dill to begin testing and improving. They started by targeting two industries: the Events Industry and Apartment Complex industry. The chatbot was designed to interact with clients in a natural and engaging way while providing them with quick and accurate responses. The chatbot was also trained to understand the language and terms commonly used in these industries.
The result of Project Dill was a successful creation of custom intelligent chatbots designed for different industries. The chatbots have proven to be effective in improving client interaction, speeding up the process, mitigating the turn around time, and eliminating the need for dedicated support teams. The chatbots designed for the Events Industry and Apartment Complex industry were well received by clients, and their engagement with the chatbots was natural and engaging. The success of Project Dill has paved the way for the development of more custom chatbots for various industries.