Retrieval Augmented Generation for Navigating Large Enterprise Documents
“If the doors of perception were cleansed, everything would appear to man as it is, Infinite.” (William Blake, The Marriage of Heaven and Hell)
As in William Blake's metaphor about the limits of mankind’s ability to perceive the reality around them, we reckon today’s business world needs clean, unbiased, easy to access lenses to unlock knowledge and insights.
To address this challenge, at Generali we have launched the development of a suite of generative tools that can query practically any business source (text, code and numbers), to retrieve fast and complete responses.
Utilizing Large Language Models (LLMs), integrated with LangChain and Vector Database, we have significantly simplified the process of navigating hundreds of documents of any corporate domain.
This session will share our journey, the experimental approaches we adopted in a few business areas and the challenges we faced while implementing a Retrieval Augmented Generation (RAG) system.
There will also be time for Q&A, so bring your questions!
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