In Legaltech News, Benjamin Joyner and Aleeza Furman explore AltaClaro’s launch of DepoSim, an AI-powered deposition simulator built in partnership with legal transcription provider Verbit, and the deposition training problem it aims to solve.
The coverage centers on a familiar constraint in litigation training: deposition skills require real reps, but hands-on opportunities can be limited because high-stakes matters leave little room for trial-and-error learning.
Joyner and Furman place DepoSim in the context of how firms have historically tried to create those reps through mock depositions, while also noting why traditional approaches can fall short. Simulations often depend on hired actors or offsite programs, which can be costly, logistically intensive, and frequently experienced as one-time events rather than repeatable practice.
Against that backdrop, DepoSim is presented as a way to make deposition training more continuous: attorneys can run realistic simulations, adjust difficulty and personalities, and receive immediate, data-driven feedback, supporting iteration and improvement without the scheduling and cost barriers of conventional mock depos.
Framed this way, the article positions AI not as a substitute for deposition experience, but as infrastructure for scaling it, turning an infrequent training exercise into a repeatable feedback loop that helps lawyers build competence faster.