In Robert Matsko v. Tesla, Inc., No. 22-CV-05240-RFL (DMR), 2025 WL 1144827 (N.D. Cal. Apr. 18, 2025), Magistrate Judge Donna M. Ryu addressed a discovery dispute centered on identifying appropriate custodians and sources of electronically stored information (ESI) in a putative class action alleging fraud related to Tesla’s self-driving features. While the court agreed that documents should be collected from five previously identified custodians, it expanded the scope to include Elon Musk and a Tesla senior director based on a sufficient showing of their likely possession of relevant information. However, the court declined to require production from three other proposed custodians, finding the plaintiff had not demonstrated that those individuals held responsive materials.
The court also delved into the boundaries of proportional and defensible discovery under Rule 26(b)(1). While allowing the plaintiff, LoSavio, to obtain responsive emails from Tesla’s designated custodians, Judge Ryu declined to compel production of other forms of electronic communications, such as text messages, until the parties had met and conferred about the feasibility and proportionality of such searches. The ruling underscored the importance of collaboration in ESI protocol development and reinforced that expanding into additional communication platforms requires concrete justification tied to relevance and burden.
Finally, the court denied LoSavio’s unilateral proposal that Tesla be ordered to run his preferred search terms. Instead, the court directed the parties to negotiate mutually acceptable search parameters and, if unsuccessful, to present evidence showing how their positions aligned with proportionality standards. For Tesla, that meant demonstrating non-responsiveness through defensible validation practices, including “quality control measures such as sampling.” The decision highlights judicial emphasis on cooperation, transparency, and data validation in modern eDiscovery—ensuring that search methodologies and custodial scopes are both targeted and defensible throughout complex data-driven litigation.
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