Serverless document automation, supercharged by Vision LLMs

## Details

An insightful session on how Vision-Based Large Language Models (LLMs) are revolutionising the extraction of information from documents. Sahil and Elaine will begin by exploring how these advanced models enable faster and more accurate data extraction compared to traditional methods with Serverless Architecture on AWS.

Next, Sahil and Elaine will delve into a case study from the insurance industry, showcasing how we reduced claim processing time for an organisation. Discover the challenges encountered, the solutions implemented, and the results achieved through the adoption of Vision LLMs powered by AWS Bedrock and Serverless computing.

Lastly, gain valuable insights into building and evaluating LLM-powered systems, along with practical next steps to enhance your document processing capabilities or explore the latest advancements in AI-driven information extraction.

Agenda
5:30 pm: Welcome & Networking
6:00 pm: Supercharge Information Extraction with Vision-Based Serverless & LLMs on AWS
6:45 Q&A
7:00 Pizza, refreshments, and Networking

About the speakers:

Sahil Bahl - Lead Data Scientist @ Mantel Group
Sahil is an AWS-certified machine learning specialist with extensive experience in Machine Learning, Generative AI, Software Engineering, and Solution Design. Passionate about empowering organisations to make informed decisions, optimise processes, and seize opportunities for growth by leveraging data and AI.

Elaine Gao - Machine Learning Engineer @ Mantel Group
Elaine is an ML engineer with a background in data engineering, with a love of the possibilities with data! I am focused on bringing AI and data-driven solutions to life. I also love taking up new hobbies and being mediocre with all of them :)