Datavault AI investors face Oct. 5 lead-plaintiff deadline in securities suit
The Law Offices of Howard G. Smith says investors with substantial losses in Datavault AI, Inc. can seek lead-plaintiff status in a class action alleging false or misleading statements.
A law firm says Datavault AI investors who lost money may seek appointment as lead plaintiff in an ongoing securities fraud class action, with an Oct. 5, 2026 deadline.
The Law Offices of Howard G. Smith said in a PR Newswire notice dated Aug. 21, 2026, that investors with substantial losses in Datavault AI, Inc. (NASDAQ: DVLT) have until Oct. 5, 2026, to ask to be appointed lead plaintiff in an ongoing securities fraud class action.
Lead-plaintiff status can affect how a securities case proceeds. The firm said class members do not need to act immediately and may retain counsel of their choice or remain absent class members.
According to the release, the complaint alleges that from Sept. 4, 2024, through Oct. 30, 2025, defendants made materially false and/or misleading statements and failed to disclose material adverse facts about Datavault AI’s business, operations and prospects. The notice also says the complaint alleges defendants deceived investors, artificially inflated and maintained the market price of Datavault AI securities, and caused class members to buy securities and options at artificially inflated prices.
The release identifies Datavault AI as the company at issue and says it concerns an ongoing securities fraud class action. It includes contact information for the firm in Bensalem, Pennsylvania, along with an email address, phone number and website for investors seeking more information.
The notice says the attorney advertisement disclaimer may apply in some jurisdictions.
No court ruling or company response was included in the PR Newswire item.
Investors who believe they fall within the alleged class period can seek lead-plaintiff appointment before the Oct. 5 deadline stated in the notice.
Sources
Editorial note: This article was prepared with AI assistance and includes source attribution for reader review.
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