Project: AI Knowledge Transfer

As people change jobs, the "tribal" knowledge they gained at their old organization is largely lost. Tribal knowledge refers to informal knowledge captured from sources like personal chats, group messages, or meeting transcripts. Could integrating AI help enhance knowledge transfer? The solution to this might involve beginners exploring the knowledge via simple AI-powered chatbots, and possibly, feedback loops on the knowledge base to understand questions being asked and the quality of answers, enabling additional refinement of the knowledge base.

Our project explores knowledge transfer in the context of NC State's student organizations and clubs. Due to the short-lived nature of most club memberships, and the tendency for clubs to use messaging platforms like Discord or Google Meet, it becomes imperative to utilize the tribal knowledge captured from these sources.

We have built a prototype using Figma that explores three distinct flows to solve our problem. The first flow depicts an event scheduler that uses AI to generate checklists of tasks that need to be performed. The next flow depicts an AI chatbot that uses past knowledge to enhance answers to commonly asked questions. Finally, the third flow allows a user to upload club files and transcripts to a document platform that would eventually be used to train the AI.

Team Members:
- Tung Tran (tatran5)
- Joshua Joseph (jjoseph6)
- Soubhagya Akkena (sakkena)
- Nitya Naga Sai Atluri (natluri)
- Feng Wang (fwang32)


Stage Reports: