At Gjensidige, Norway’s largest insurer, one of the most important tasks for analysts and data scientists is the interactive visualization and simulation of our data. In use cases such as risk prediction and asset management, we have established the Python-based package Streamlit as our preferred frontend for data-driven applications. In this talk, I will walk you through the process of rapid LLM prototyping using OpenAI and Streamlit to create chatbots that heavily increase the efficiency of our internal processes. You will meet “”Eglev””, our innovative chatbot designed to empower without displacing tasks. Learn how we turned Eglev from idea to working demo with greater than 91% accuracy in only 6 weeks. By making our lakehouse data available for non-technical resources by predicting SQL queries from natural language, Eglev allows our data scientists to focus on the most important tasks.
Talk By: Alexandra Diem, Head of AI & MLOps, Gjensidige
Here’s more to explore:
LLM Compact Guide: https://dbricks.co/43WuQyb
Big Book of MLOps: https://dbricks.co/3r0Pqiz
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