Datavault AI: Fresh Capital, Blue Chip Partnership Back A Speculative Buy

Summary DVLT is an early-stage AI and Web3 play focused on building AI agents for data visualization and monetization, as well as tokenization and trade of real-world assets. The key near-term catalysts are the $150M strategic investment from Scilex, and the IBM partnership. Sales are currently low at $1.7 million in Q2, but sales guidance for 2026 lies between $40M–$50M, achievable with IBM integration and platform expansion. Key risks include high cash burn, early-stage execution risk, reliance on strategic investor, speculative valuation. Datavault AI (NASDAQ: DVLT ) has been showing strong momentum lately, yet still seems to be under-the-radar. In fact, DVLT has been less covered here on Seeking Alpha, even when it was still trading as WiSA Technologies, which acquired then-Data Vault Holdings’ assets late last year, and rebranded as Datavault AI early this year. The recent price surge, which has been fueled mainly by the large strategic investment it secured recently from Scilex Holding ( SCLX ), coupled with Datavault’s expanding and diversified IP portfolio (which now holds 72 patents), licensing opportunities, high-value partnerships and integrations, and other tech initiatives in Web3 and AI, together set DVLT up as a promising but speculative growth play. While the tech stack is promising and the commercial roadmap remains early, the recent Scilex investment worth $150 million, of which the first tranche of $8 million have been closed and paid in Bitcoin ( BTC-USD ), is the first main pillar for the renewed confidence in DVLT and the speculative Buy thesis in this piece. Datavault AI - Understanding the Company and Business Models Datavault AI is a data and AI tech company that is building an integrated platform that transforms underutilized enterprise and consumer data into structured, monetizable assets. While data visualization and monetization are the focal points for Datavault, the company also retains some legacy exposure from WiSA’s audio IP. I think big opportunities are opening here as data becomes a financial asset in its own right and as AI agents move from experiments to core infrastructure for enterprise workflows and decentralized applications. Datavault operates through two divisions: the Data Science and the Acoustic Science divisions, both building products and an IP portfolio that straddles enterprise data monetization, Web3 infrastructure, and advanced wireless audio. The Data Science division is focused on Datavault's AI agents - DataScore, DataValue, and the Data Vault Bank. These agents operate in a workflow to provide enterprises with risk scoring, data valuation, and eventually the ability to structure and trade data as assets. Company website These agents run on Datavault’s Information Data Exchange platform, which integrates blockchain-based tokenization, immutable metadata indexing, digital twins, and NIL licensing, making it possible for clients to assign value, enforce ownership, and generate revenue streams from their datasets. Behind Datavault's AI agents and data exchange platform is a high-performance computing [HPC] infrastructural backbone that powers the agents and the platforms and links into Datavault’s blockchain-based architecture, enabling fast tokenization and immutable metadata indexing without bottlenecks. That infrastructural backbone has been seeing integrations for enterprise-ready deployments and scaling, with Datavault already advancing key integrations of its flagship AI agents Data Vault Bank, DataScore, and DataValue with IBM’s ( IBM ) watsonx.ai framework, being a platinum Partner in the IBM Partner Plus program. This integration further provides Datavault with enterprise-grade tooling for pricing and client engagement, making its products more market ready. The IBM endorsement and the distribution channels it opens for commercialization form the second pillar of the speculative Buy case in this piece. While most of the momentum DVLT is seeing lately is building around the AI and data business prospects, the Acoustic Science division also remains an important strategic asset and a direct revenue channel. In fact, a chunk of the patent licensing bookings worth $2.5 million reported together with the Q2 results came from licensing of the ultrasonic Ad delivery platform branded as ADIO to a digital Ad exchange platform called NYIAX, which falls under the umbrella of the Acoustic Science division. The division carries forward the legacy WiSA audio IP, including wireless multichannel audio technologies under the WiSA, ADIO, and Sumerian brands. This side of the business generates licensing opportunities through hardware integrations and advertising, most notably with the ADIO inaudible-tone advertising platform that has already been licensed to NYIAX. By combining acoustic IP with data monetization infrastructure, Datavault is potentially positioning at the convergence of digital and physical channels, creating multiple monetization vectors. The acoustic portfolio legacy assets could still offer licensing or integration opportunities. It preserves wireless audio IP which could be paired with AI-driven applications for immersive environments, spatial audio, or Web3 and Metaverse integrations, if it gains traction in the future. Beyond the AI agents and platform that form the core tech stack, the IBM integration, and the diversified IP portfolio already active and ripe for commercialization, Datavault has hinted at launching three new exchanges later this year focused on tokenization of real world assets and event-driven markets, which are branded as the International Elements Exchange, the International NIL Exchange (which is based on Name, Image, and Likeness rights, with real athlete NIL assets already monetized), and the American Politics Exchange. We've seen the traction which the decentralized prediction market platform Polymarket has achieved since its launch, with daily volumes sometimes crossing tens of millions of dollars. Hence, the potential market opportunity and revenue upside here for Datavault. Datavault's Early-Stage Momentum Meets Speculative Valuation Latest financial results from Datavault (Q2 2025) show a company still in transition. Revenue for Q2 came in at $1.7 million, up sharply from $630k in Q1, bringing H1 sales to $2.33 million. In Q1, management guided for $12 million to $15 million sales in H2 2025 , and an update of that target is one of the near-term financial milestones investors should look out for. Gross margin improved sequentially, but the company still ran an operating loss, because of high investment in scaling the AI and Web3 infrastructure. Operating expenses was $12.49 million with R&D and general and administrative expenses making up the bulk of these costs; they accounted for roughly 86% of total OpEx in Q2, and were the primary driver of the ~$12.5 million loss from operations. Controlling operating expenses will be key to managing cash burn. Cash on hand remains limited at just shy of $650k as of Q2 end, which makes the $150 million investment from Scilex an important infusion and ample drypowder for scaling. DVLT is one of those early-stage AI plays where investors with high risk threshold would turn a blind eye to valuation multiples. Sales are paltry compared to the rising valuation, and profitability is non-existent. DVLT currently trades at 12.5x P/S. It is worth mentioning that DVLT’s current valuation multiples are still calculated against the legacy WiSA sales base, since the company only acquired Data Vault Holdings’ assets late last year. An adjusted calculation of P/S based on Q1 and Q2 sales only ($630k in Q1 and $1.7 million in Q2, or $2.33 million in H1) would put P/S around 27x, at the current $127 million market cap. This isn’t the standard trailing twelve month metric, but an illustration to better capture how stretched DVLT’s valuation might be to sales. Data by YCharts Even with this adjusted calculation, I think valuation isn’t very high for a speculative AI and Web3 play that is undercovered and has already seen key integrations and is positioned for commercialization. If we consider how quantum stocks, for example, traded at insanely high multiples (some traded over 1000x P/S) during their discovery phase late last year (a phase which I believe DVLT is currently in), and now some of those quantum stocks that have seen higher sales numbers and trade at far more rational multiples. Though they are still expensive compared to established companies, this is the premium investors typically pay for vision and speculation. I believe this is likely a similar dynamic for DVLT. Datavault’s management has outlined sales guidance between $40 million to $50 million for 2026, which the IBM integration ( re-affirmed today based on the latest press release ), and platform expansion put the target in achievable territory, in my view. Risks Key risks remain for DVLT despite the momentum. Revenue is still limited, profitability is non-existent, and operating expenses are high, driving substantial cash burn. Execution risk is significant, as scaling AI agents, exchanges, and Web3 infrastructure depends on timely execution and adoption. Reliance on a single strategic investor at this stage and early-stage commercial integrations adds concentration risk, while valuation remains stretched relative to current sales, which leaves little margin for missteps. Takeaway At this stage, the two main catalysts are: the $150 million investment from Scilex, which provides DVLT with balance sheet strength and validation at a stage when most peers struggle for funding. That capital also opens optionality in scaling its agents and exchanges. And the IBM watsonx.ai integration, which gives DVLT a commercialization pathway with blue-chip enterprises. While highlighting the promising tech stack of Datavault and the prospects, I've pointed out the speculative nature of this play. Execution remains key and will determine whether potential translates into value.