How can AI be used for legal research purposes by legal teams?
Artificial intelligence is changing how legal teams conduct research by making large volumes of court data searchable, structured, and comparable. In state trial courts—where data has historically been fragmented and difficult to access—AI can aggregate records across jurisdictions and extract key information from filings, motions, and rulings.
This allows attorneys to go beyond basic case lookup and instead analyze patterns. Legal teams can evaluate how judges rule on specific motions, track opposing counsel’s litigation history, and assess how similar cases have progressed over time. These insights support more informed decisions around case strategy, timelines, and risk.
Platforms like Trellis apply techniques, such as natural language processing and machine learning, to structure unorganized legal data and make it usable for research and analysis. By turning raw court records into structured datasets, AI enables a shift from manual research to data-driven legal analysis.
In this episode of The Law of Tech Podcast, Nicole Clark, co-founder and CEO of Trellis, discusses how AI is being used in legal research and how access to state trial court data is changing the way legal teams approach their work.