Unleashing the power of Generative AI for Intelligent Document Processing -- AWSInsider

Unleashing the power of Generative AI for Intelligent Document Processing

Date: Thursday, September 26^th at 11am PT / 2pm ET

Paper piles are a thing of the past. Organizations are seeking innovative ways to optimize their paper-based business processes and reduce costs. In this upcoming webinar, we will explore how Intelligent Document Processing (IDP) powered by Generative AI (GenAI) can unlock additional business value for a variety of industries, including lending, insurance, and healthcare.

During this session, you will learn how AWS services like Amazon Bedrock, Textract, and Comprehend can help you augment and automate manual workflows that are often time-consuming for roles such as business analysts and research associates. By leveraging GenAI-powered IDP, organizations have been able to improve employee productivity and decrease costs simultaneously, accelerating their business growth and profitability.

Key topics that will be covered include:

How GenAI can enhance IDP workflows to optimize paper-based processes
Use cases for leveraging GenAI to unlock additional value in lending, insurance, and healthcare
Strategies for integrating GenAI-powered IDP solutions to boost efficiency and reduce costs
Real-world examples of organizations that have successfully implemented GenAI-powered IDP

Don't miss this opportunity to learn how your organization can harness the power of Generative AI and Intelligent Document Processing to drive business growth and profitability. Register now for this informative webinar.

Register now!

About the presenters:

Ryan Ries, Chief Data Science Strategist, Mission Cloud Services

Dr. Ryan Ries is a highly accomplished data scientist and engineering leader with over 15 years of experience in the technology industry. He is recognized as an AWS Data and Machine Learning expert. Currently, he serves as the Chief Data Science Strategist at Mission Cloud.

Date: 09/26/2024

Time: 11:00 AM PT

Duration: 1 Hour

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