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VisionWave Files U.S. Non-Provisional Patent Application for DeepWave RF™, an AI-Powered Subsurface Sensing and Visualization Platform

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VisionWave (Nasdaq: VWAV) filed a U.S. non-provisional utility patent application (No. 19/752,680) for its DeepWave RF™ subsurface sensing and visualization platform on July 24, 2026, naming CTO Dr. Danny Rittman as first inventor and claiming priority to an April 8, 2026 provisional filing.

DeepWave RF™ integrates software-defined radio, near-bit RF sensing, edge computing, and physics-informed AI to analyze electromagnetic signals near the drill bit and generate probabilistic, 2D/3D look-ahead visualizations. The system is being developed for drilling, geothermal, mineral, water, and other subsurface applications, though VisionWave cautions there is no assurance a patent will be granted.

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Market Context

The five-event AI-tag record averaged -1.27%, adding historical context to this filing. The announce...
Analysis

The five-event AI-tag record averaged -1.27%, adding historical context to this filing. The announcement remains subject to patent-issuance uncertainty; formation conductivity, drilling fluid, and antenna configuration are stated technical limitations to monitor.

Key Figures

U.S. patent application number: 19/752,680 Filing date: July 24, 2026 Provisional application number: 64/032,626 +2 more
5 metrics
U.S. patent application number 19/752,680 DeepWave RF non-provisional utility patent application
Filing date July 24, 2026 U.S. Patent and Trademark Office filing
Provisional application number 64/032,626 Priority application filed April 8, 2026
Priority filing date April 8, 2026 U.S. provisional patent application
Look-ahead sensing distance Tens-of-meters range Favorable resistive formations

Previous AI Reports

5 past events · Latest: Jul 14 (Positive)
Same Type Pattern 5 events
Date Event Sentiment 24h Move Catalyst
Jul 14 AI patent filing Positive -0.9% Provisional filing for SkyWeave satellite-free AI communications ecosystem
Jun 15 AI patent filing Positive +1.0% Provisional filing for SDNN autonomous defense AI architecture
May 06 AI platform integration Positive +6.2% xCalibre AI integration into Solar Drone autonomous flight platforms
Apr 28 AI patent filing Positive -4.6% Provisional filing for xCalibre camera-as-sensor AI platform
Apr 21 AI strategic investment Positive -8.1% Strategic investment and xClibre AI video intelligence integration

24h Move is the share-price change in the day after each event; other market factors may also have contributed.

Pattern Detected

AI-tagged announcements produced mixed reactions, with three of five selected events diverging from the positive nature of the announcements.

Key Terms

non-provisional utility patent application, software-defined radio, physics-informed neural networks, maxwell’s equations
4 terms
non-provisional utility patent application regulatory
"filed a U.S. non-provisional utility patent application relating to its DeepWave RF technology"
A non-provisional utility patent application is the formal, full filing submitted to a patent office that describes an invention, its technical details, and the legal claims that define what the inventor wants protected; it begins the official examination process that can lead to an issued utility patent. For investors, it signals a company is seeking legally enforceable exclusive rights to an invention—an intangible asset that can affect competitive position, licensing potential, and company valuation, much like staking a legal claim on a piece of intellectual property.
software-defined radio technical
"integrates a software-defined radio platform with the drill string or bottom-hole assembly"
A software-defined radio is a radio system where functions traditionally done by fixed hardware—like tuning, filtering and decoding signals—are performed by software running on general-purpose processors. For investors, it matters because this flexibility can cut development costs, speed product updates, expand applications across markets, and concentrate value in software and services rather than specialized chips, while also raising considerations about regulatory compliance and cybersecurity.
physics-informed neural networks technical
"architecture may use physics-informed neural networks, or PINNs"
Physics-informed neural networks are computer models that learn patterns from data while being guided by known physical laws or equations, like a student taught both from examples and a rulebook. They matter to investors because they can produce more reliable and efficient predictions for engineering, energy, or drug development problems, reducing uncertainty, speeding product development, and potentially lowering costs and risk compared with purely data-driven models.
maxwell’s equations technical
"that incorporate Maxwell’s equations into the learning and inversion process"
A set of four fundamental equations that describe how electric and magnetic fields are generated and interact, governing light, radio waves, and electrical currents. Think of them as traffic rules for electromagnetic forces: they explain how charges create fields, how changing fields produce each other, and how fields move through space. They matter to investors because they underpin technologies across communications, power, sensors, semiconductors, and optics, which drive many industries and product capabilities.

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Proposed technology integrates software-defined radio, near-bit RF sensing, edge computing, and physics-informed artificial intelligence intended to provide drilling operators with actionable intelligence about subsurface conditions ahead of the drill bit

WEST HOLLYWOOD, Calif., July 29, 2026 (GLOBE NEWSWIRE) -- VisionWave Holdings, Inc. (Nasdaq: VWAV) (“VisionWave” or the “Company”), today announced that it has filed a U.S. non-provisional utility patent application relating to its DeepWave RF™ technology, an advanced subsurface sensing and visualization platform designed for drilling, geological exploration, and related industrial applications.

The application, U.S. Patent Application No. 19/752,680, is titled “Systems and Methods of Integrated Software-Defined Radio and Drilling for Near-Bit Subsurface Sensing and Visualization.” The application was filed with the United States Patent and Trademark Office on July 24, 2026, and identifies Dr. Danny Rittman as the first named inventor.

The filing is a non-provisional application claiming priority to U.S. Provisional Patent Application No. 64/032,626, filed April 8, 2026 (titled as - NEAR-BIT SUBSURFACE RF SENSING SYSTEMS). No assurance can be given that a patent will be issued from either application or, if a patent is issued, as to the scope of any claims that may ultimately be allowed.

DeepWave RF™ is being developed to address one of the drilling industry’s most persistent challenges: the limited ability to understand geological formations before the drill bit physically reaches them. Conventional logging-while-drilling systems primarily measure conditions surrounding the drilling assembly. DeepWave RF™ is designed to shift that model toward anticipatory sensing by examining the formation directly ahead of and around the drill bit.

The proposed architecture integrates a software-defined radio platform with the drill string or bottom-hole assembly, together with a near-bit antenna system, adaptive RF waveform control, edge processing, and an AI-assisted hybrid inversion engine. The system is designed to process received electromagnetic signals and convert them into a probabilistic representation of the subsurface formation.

Rather than transmitting large volumes of raw downhole data to the surface, DeepWave RF™ is intended to perform critical processing close to the point of measurement. Its AI architecture may use physics-informed neural networks, or PINNs, that incorporate Maxwell’s equations into the learning and inversion process. This approach is designed to accelerate subsurface interpretation while helping ensure that AI-generated results remain consistent with known electromagnetic physics.

The platform is intended to identify and characterize subsurface features such as:

  • Fractures and fracture corridors
  • Geological and lithological boundaries
  • Voids and cavities
  • Gas-related anomalies
  • Fluid contacts and water-bearing zones
  • Changes in rock properties
  • Mineralized or metal-bearing structures

DeepWave RF™ may provide operators with information such as the estimated range and direction of an anomaly, its probable classification, and an associated confidence level. The resulting information may be presented as a dynamic two-dimensional or three-dimensional look-ahead visualization, a 360-degree subsurface view, a hazard alert, or a confidence-ranked geological map.

“DeepWave is designed to give drilling teams something the industry has pursued for decades: meaningful visibility into the formation before the drill bit reaches it,” said Dr. Danny Rittman, Chief Technology Officer of VisionWave and first named inventor. “By combining software-defined radio, advanced signal processing, and physics-informed artificial intelligence at the edge, we aim to transform drilling from a largely reactive process into a more predictive, intelligent, and safety-focused operation.”

The system is designed to adapt its RF sensing parameters to changing geological and drilling conditions. In favorable resistive formations, the architecture described in the application is designed to achieve look-ahead sensing distances in the tens-of-meters range with improved structural detail. Actual range and resolution would depend on formation conductivity, dielectric properties, drilling fluid, antenna configuration, and other operating conditions. The patent application expressly recognizes that highly conductive formations may substantially reduce achievable RF penetration.

Potential benefits of the DeepWave RF™ platform, if the technology is successfully developed and commercialized, could include improved geosteering, earlier detection of drilling hazards, reduced risk of unexpected formation changes, improved reservoir-zone navigation, and better-informed decisions during drilling operations. The technology could also help operators distinguish between broad geological boundaries and discrete structures such as fractures, voids, or localized gas pockets.

Although oil and gas drilling represents an important potential application, the technology is designed for a broader range of subsurface industries, including geothermal energy, mineral exploration, water detection, salt navigation, deepwater drilling, geological surveying, archaeological exploration, and paleontological investigation.

The filing represents another step in VisionWave’s strategy of combining artificial intelligence, radio-frequency sensing, edge computing, and advanced visualization to address complex industrial and infrastructure challenges.

About VisionWave

VisionWave Holdings, Inc. (Nasdaq: VWAV) is a defense and advanced sensing technology company developing AI-driven, RF-based sensing, autonomy, and computational acceleration technologies for defense, homeland security, and commercial infrastructure applications. VisionWave's mission is to connect defense innovation with civilian progress through shared core technologies deployed across air, land, and fixed-site environments. The Company's website is https://www.vwav.inc.

Forward-Looking Statements

This press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995 and Section 21E of the Securities Exchange Act of 1934, as amended, including statements concerning the anticipated development, capabilities, performance, commercialization, and potential applications of DeepWave RF™ and the prosecution and potential outcome of the Company’s pending patent applications. These statements are based on current expectations and assumptions and are subject to risks and uncertainties that could cause actual results to differ materially. Forward-looking statements are generally identified by words such as “believe,” “may,” “will,” “estimate,” “continue,” “anticipate,” “intend,” “expect,” “should,” “would,” “plan,” “project,” “forecast,” “predict,” and similar expressions, or by statements that events or trends “may,” “will,” or “could” occur. Forward-looking statements are subject to risks and uncertainties that could cause actual results to differ materially from those expressed or implied, including, but not limited to, the risk that no patent may be issued from the Company’s pending patent applications, or that any patent that is issued may not provide meaningful protection; the early stage of development of DeepWave RF™ and the risk that the technology may not achieve the performance characteristics described in the patent application or any particular commercial result; the Company’s ability to fund continued development and commercialization of the technology; competition from companies with substantially greater resources; and other risks described in the Company’s filings with the U.S. Securities and Exchange Commission. All forward-looking statements speak only as of the date of this press release and are expressly qualified in their entirety by the cautionary statements included in this press release and in the Company’s SEC filings. VisionWave undertakes no obligation to update or revise any forward-looking statements, whether as a result of new information, future events, or otherwise, except as required by law. Investors are cautioned not to place undue reliance on these forward-looking statements.

Contact: investors@vwav.inc


FAQ

What did VisionWave (Nasdaq: VWAV) announce about its DeepWave RF patent on July 29, 2026?

VisionWave announced it filed a U.S. non-provisional utility patent application for its DeepWave RF™ subsurface sensing platform. According to VisionWave, the application (No. 19/752,680) was filed July 24, 2026, and claims priority to an April 8, 2026 U.S. provisional application.

What is VisionWave’s DeepWave RF™ AI-powered subsurface sensing platform for VWAV investors?

DeepWave RF™ is being developed as an AI-assisted subsurface sensing and visualization platform for drilling and geological exploration. According to VisionWave, it combines software-defined radio, near-bit antennas, edge processing, and physics-informed neural networks to convert RF signals into probabilistic 2D and 3D look-ahead formation visualizations.

How does DeepWave RF™ use AI and physics-informed neural networks, according to VisionWave (VWAV)?

DeepWave RF™ may use physics-informed neural networks that embed Maxwell’s equations into the learning and inversion process. According to VisionWave, this approach is intended to accelerate interpretation of RF data while helping keep AI-generated subsurface models consistent with established electromagnetic physics and drilling conditions.

What subsurface features is DeepWave RF™ designed to identify for VisionWave’s target industries?

DeepWave RF™ is intended to detect features such as fractures, boundaries, voids, gas-related anomalies, fluid contacts, and mineralized structures. According to VisionWave, the system may estimate range, direction, classification, and confidence levels, presenting results as look-ahead views, hazard alerts, or ranked geological maps.

Which industries could use VisionWave’s DeepWave RF™ technology beyond oil and gas drilling?

According to VisionWave, potential applications for DeepWave RF™ include geothermal energy, mineral exploration, water detection, salt navigation, deepwater drilling, geological surveying, archaeological exploration, and paleontological investigation. The platform is being designed as a flexible subsurface sensing tool across multiple industrial and scientific sectors.

Does filing the DeepWave RF™ patent guarantee VisionWave (VWAV) will receive patent protection?

Filing the non-provisional application does not guarantee issuance of a patent. According to VisionWave, no assurance can be given that any patent will be granted or, if issued, what the ultimate scope of allowed claims and legal protection might be.