Most state trial court intelligence has historically lived in attorneys’ inboxes, internal notes, and anecdotal conversations—not in searchable systems.
That creates a real strategic blind spot. How does a particular judge tend to rule? How often has opposing counsel argued this issue? What motion patterns emerge across similar cases?
Trellis was built to answer those questions.
In this episode of the AI in Action podcast, Nicole Clark, CEO and co-founder of Trellis, explains how the company turned fragmented state trial court data into structured legal intelligence that attorneys can actually use.
Founded in 2017, Trellis is a legal research and analytics platform focused on state trial courts, giving legal teams searchable access to judges, dockets, motions, opposing counsel history, and case outcomes.
Before founding Trellis, Nicole practiced as a business litigator and labor & employment attorney in both state and federal court. Like many litigators, she found herself relying on internal emails and colleague anecdotes to make strategic recommendations about judges and litigation approach. Trellis started as a solution to that problem.
In the conversation, Nicole discusses:
- why state trial court data has been so difficult to access
- the early challenges of building Trellis
- how legal teams use judicial and litigation analytics today
- what life looks like on the engineering team
- where legal AI and analytics are headed
- why Trellis is building for this market