A company's knowledge bases often times don't answer the wide variety of questions a user could come up with. A Customer Support system ideally could answer specific (but wide variety) questions about the company's systems and knowledge (example: "How can I enter Cash Flow in ThruThink?"). But sometimes the user asks generic questions, such as "What is Cash Flow?" which could be sourced from the mind of a giant LLM model and / or the internet. My idea is to help and boost the performance by leveraging Question and Answer generation techniques - normally used for fine tuning but in this case - for knowledge base augmentation / indexing enrichment. The generated questions could support specific user queries potentially better matching than a "non focused" indexed generic knowledge base.
Category tags:"Nice use of Vectara and the synthetically generated Q&A. "
Ofer Mendelevitch
Head of DevRel
"Good overview of the architecture. And good idea of combining generic information with specific information from a knowledge base. "
Justin Hayes
Head of Field Engineering