We began with pain points in mind

Depositions are crucially important to winning cases and depo prep can be overwhelming.

Not having a live transcript means it can be difficult to catch deponents in their contradictions or half truths during a deposition (particularly in long, multi-day depositions).

Trying to develop follow-up questions on the fly, in addition to tracking your deposition goals and managing all the variables presented by a deposition, can sometimes feel impossible.

Spending thousands of dollars for a court reporter and waiting two weeks to receive a depo transcript is both annoying and inefficient.

We solved those problems. And a few others while we were at it.

Here’s how it works:

You create a new case in our software, let our AI language model, Ava, know whether you represent the plaintiff(s) or defendant(s), and upload relevant case documents.

Ava then analyzes your documents and will generate suggested deposition goals, draft proposed deposition questions, and identify any opportunities or weaknesses in your case. Ava will also let you know what questions you should likely prepare for if you represent the person being deposed.

As you upload more documents, Ava continues to evolve and learn so as to continuously provide you with new, actionable insights.

During each deposition you’ll get a live, searchable transcript. Ava will use that live transcript to (i) track whether you are accomplishing your selected goals, (ii) provide follow-up questions you can employ mid-deposition, (iii) identify inconsistencies and ambiguities (both within deposition testimony and deposition testimony compared to case documents) and (iv) highlight ambiguous answers or unanswered questions.

When you are done with a deposition, you’ll have a succinct PDF summary of the deposition and a PDF file of the entire deposition transcript. Both PDF files (the summary and the transcript) will be saved to the applicable case file within the software.

Meet the Team

  • Dr. David Wingate

    THE BIG BRAIN

    David Wingate, PhD, is a computer science professor at BYU and one of the nation’s foremost AI machine learning experts. After receiving his PhD in computer science from the University of Michigan he spent three years as a postdoctoral fellow at the MIT Artificial Intelligence Lab.

    Following his fellowship, Dr. Wingate worked for another three years as a research scientist at MIT in the Brain and Cognitive Sciences Department and the Laboratory for Information and Decision Systems. Dr. Wingate has published extensively in machine-learning related fields and has contributed foundational work in probabilistic programming.

  • Andrew Applegate

    THE LAWYER

    Andrew is a lawyer and entrepreneur that enjoys streamlining processes and solving problems. He understands the unique challenges presented by the practice of law and is dedicated to helping modernize the legal field.

  • Keeton Hodgson

    THE DEVELOPER

    Keeton Hodgson is an ex-Amazon software engineer that helped build Amazon’s AWS storage system. Following his time at Amazon, Keeton was a member of the founding developer team at Leland, a rapidly growing online coaching platform for Ivy-league hopefuls.