Technically Legal - A Legal Technology and Innovation Podcast

Author: Percipient - Chad Main

Technically Legal is a legal tech podcast exploring how technology is transforming the legal landscape. Each episode features insightful interviews with legal innovators, tech pioneers, and forward-thinking educators who are leading this change. Our guests share their experiences and insights on how technology is reshaping legal operations, revolutionizing law firm practice, and driving the growth of innovative legal tech companies. We also explore the broader implication of technology on everyone involved in the legal system, from practitioners to clients. The podcast is hosted by Chad Main, an attorney and founder of Percipient, a tech-enabled legal services provider. Chad launched Percipient on the belief that when technology is leveraged correctly, it makes legal teams more effective. Technically Legal Podcast is an ABA Web 100 Best Law Podcasts Honoree.
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Language: en

Genres: News, Tech News, Technology

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On AI Evals, TAR vs. LLMs and What Will be Different Next Year - Aron Ahmadia (VP Applied Science, Relativity)
Thursday, 17 September, 2026

In advance of this year's RelFest in Chicago, Aron Ahmadia, Vice President of Applied Science at Relativity, joins the podcast to discuss AI evaluation, AI benchmarking and the transition from traditional Technology Assisted Review (TAR) to generative AI in legal document review and eDiscovery. The conversation covers the daily operations of a global AI team, the concept of "evaluation as a product," and the methodology behind testing large language models (LLMs) for legal tasks. Aron also discusses a recent study that compared the accuracy and efficiency of TAR and human document review against Relativity's generative AI tool, aiR for Review. Aron talks about: A day in the life of the VP of Applied Science at Relativity. Navigating the rapid pace of AI and predicting what remains constant in legal tech. Aron's background: From early computer networking in a law firm to data science at DARPA and Capital One. Defining "evaluation as a product" and the importance of maintaining private benchmarks for LLMs. The trade-offs between human evaluations and automated AI evaluations. TAR (Predictive Coding) versus Generative AI: How prompt-based reasoning differs from label-based classification. Episode Credits Editing and Production: Grant Blackstock Theme Music: Home Base (Instrumental Version) by TA2MI