Iowa Technology Summit 2025 — Innovation Track — 11:10 AM
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Structuring the Unstructured: GenAI Data Transformation
INNOVATION TRACK / INTERACTIVE PRESENTATION

ROOM 312-313 / APR. 8 / 11:10 AM - 12:00 PM
About this session

Do you have unstructured data sitting around that you can’t get value out of? Let’s turn it into something useful! Learn how to navigate pesky mixed-media pdfs and use few shot prompting with images to improve data accuracy.

This session will cover techniques used to convert problematic unstructured documents into structured data you can look at in aggregate and use to drive decision making. We’ll cover a few different real-world document types, and a step by step approach of how each technique solves certain problems. After we build up a local example and cover questions, we will look at what a scaled cloud native version of a solution like this might look like, as well as cases it could be applied to.

 We will use techniques like:

 – Multi modal models
 – Image based few shot prompting
 – Structured LLM outputs
 – Evaluations

Key takeaways

1. What do I do when my unstructured data is too messy for out of the box tools?

2. How to leverage image based few shot prompting to improve accuracy

3. Setting this type of solution up at scale

Speaker
Grey Lovelace
Sr. Software Consultant, Coach. & GenAI Specialist
Source Allies​

Grey Lovelace is a Sr. Software Consultant at Source Allies. He is known for building reusable and resilient solutions in many industries, including insurance, financial services, and agriculture. Grey has built applications with hundreds of different integration points and of different use cases for over a decade, and has experienced first hand what works, and what doesn’t stand the test of time.

He takes pride in designing sustainable architecture that can thrive in the real-world, where things do not always go as planned. The last few years, Grey has been focused on Generative AI, finding real solutions to real problems in a space that is often filled with more noise than substance.

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