[Webcast] How Academic-Centric AI Projects are Driving Legal Tech R&D

When organizations lack the resources to rigorously test cutting-edge AI tools, who fills the research gap? A collaboration between Worcester Polytechnic Institute (WPI), HaystackID®, and Relativity® demonstrates how academic partnerships can accelerate innovation. A team of WPI undergraduates conducted comprehensive benchmarks of large language models (LLMs) and developed a working prototype for AI-driven legal document classification.

The nine-month project tackled real challenges facing eDiscovery professionals: how do different LLMs perform on legal datasets, what processing methods yield the highest accuracy, and how can confidence thresholds improve classification reliability? The students evaluated over 10 models, introduced novel enhancements to hypergraph neural networks, and built a live web application that achieved 94% accuracy with Claude 3.7 Sonnet—surpassing many industry benchmarks.

This webcast will explore the practical insights emerging from academic-industry collaboration, including zero-shot prompting techniques and document length optimization, as well as the finding that documents without unique keywords often classify more accurately than those with specialized legal terminology. Beyond the technical results, the project exemplifies a scalable model for legal tech R&D that benefits both industry partners seeking rigorous testing and academic institutions preparing the next generation of AI-literate legal professionals.

Attendees will learn about:

• Real-world testing of Claude 3.7, o3-mini, and Qwen2.5 on legal datasets.
• Lessons in zero-shot prompting, model confidence, and topic accuracy.
• How academic partnerships can accelerate R&D and platform innovation.
• Strategies to build the next generation of AI-literate legal professionals.

Webcast Details 

+ Original Date: Wednesday, November 19, 2025

Expert Panelists  

+ Aron Ahmadia, PhD

Senior Director, Applied Science at Relativity

Aron is the Senior Director for Applied Science at Relativity, where he leads the development of AI capabilities for Relativity One, including AI-Assisted Review, Analytics, and Search. He is an internationally recognized expert on machine learning and artificial intelligence. His specializations include the use of AI in Legal Discovery, Model Risk Management, and Responsible AI. Aron holds a Ph.D. in Applied Math from Columbia University and a B.S. in Computer Engineering from the Illinois Institute of Technology.

+ Roee Shraga, PhD

Assistant Professor, Computer Science, WPI

Before joining WPI, Roee Shraga was a Postdoctoral fellow at the Khoury College of Computer Science at Northeastern University in Boston. His research mainly revolves around data discovery and integration, and combines techniques from data management, machine learning, information retrieval, and human-in-the-loop. His research has been published in top-tier conferences such as SIGMOD, VLDB, SIGIR, WWW, and ICDE. He is a recipient of the Council for Higher Education [VATAT] scholarship for outstanding data science postdocs. He is also a recipient of several PhD fellowships, including the Leonard and Diane Sherman Interdisciplinary Fellowship (2017), the Daniel Excellence Scholarship (2019), and the Miriam and Aaron Gutwirth Memorial Fellowship (2020).

+ John Brewer [Moderator]

Chief Artificial Intelligence Officer and Chief Data Scientist, HaystackID

As HaystackID’s Chief Artificial Intelligence Officer and Chief Data Scientist, John focuses on bringing the latest advancements in artificial intelligence and data science technologies to the eDiscovery and incident response markets. Having worked with HaystackID since 2015, Brewer has been a software engineer and information technologist for over two decades, with experience spanning dozens of Fortune 500 companies in technology leadership roles, including eDiscovery, data migration, and information stewardship. Brewer has also been at the forefront of new data technology throughout his career. He spearheaded HaystackID’s adoption of large-scale technology-assisted review, positioning the company as one of the first to embrace this transformative approach. Recognizing the need for efficient processing in the face of the aggressive timelines associated with breach work, Brewer played a pivotal role in developing the suite of AI-based machine learning tools that power HaystackID’s review process, including his recent work on Protect Analytics AI™, an AI-enabled platform that can precisely identify and classify a wide array of internationally sensitive data types and entities.

About HaystackID®  

HaystackID solves complex data challenges related to legal, compliance, regulatory, and cyber events. Core offerings include Global Advisory, Data Discovery Intelligence, HaystackID Core® Platform, and AI-enhanced Global Managed Review powered by its proprietary platform, ReviewRight®. Repeatedly recognized as one of the world’s most trusted legal industry providers by prestigious publishers such as Chambers, Gartner, IDC, and Legaltech News, HaystackID implements innovative cyber discovery, enterprise solutions, and legal and compliance offerings to leading companies and legal practices around the world.  HaystackID offers highly curated and customized offerings while prioritizing security, privacy, and integrity. For more information about how HaystackID can help solve unique legal enterprise needs, please visit HaystackID.com.    

Assisted by GAI and LLM technologies.   

Source: HaystackID