VisionWave Holdings Files Provisional Patent for Advanced Symbiotic Deep Neural Network Architecture

VisionWave Holdings, Inc. (Nasdaq: VWAV), a company focused on advanced sensing, artificial intelligence, imaging, and autonomous technologies, announced the filing of U.S. Provisional Patent Application No. 64/082,410. This application covers its proprietary Symbiotic Deep Neural Network (SDNN™) architecture, which is designed to support real-time multi-source fusion, adaptive reasoning, and coordinated control of distributed intelligent platforms across multiple sectors including defense, security, counter-unmanned aerial systems (UAS), robotics, and civil infrastructure.

The SDNN™ architecture is intended as a central reasoning and coordination layer for networks of distributed intelligent systems. Internally, VisionWave refers to the core layer of this architecture by the project code name "Mother." The provisional patent submission includes a detailed 455-page specification supported by 23 engineering drawings, marking one of the company’s most extensive intellectual property filings to date.

SDNN™ aims to integrate data from heterogeneous sensors such as radio frequency (RF), radar, electro-optical/infrared (EO/IR), thermal sources, as well as software agents, unmanned ground vehicles (UGVs), unmanned aerial vehicles (UAVs), satellite feeds, and relay nodes. The system supports adaptive reasoning, confidence evaluation, coordinated tasking, and human-governed decision workflows across distributed operational networks.

The architecture operates as a closed intelligence loop following the sequence: Intent -> Reason -> Task -> Execute -> Feedback -> Adapt -> Repeat. Key technology components described in the filing include:

- Multi-source data fusion that continuously updates the operational state by integrating diverse sensor and software-agent data streams.

- The qSpeed™ reasoning engine, a proprietary framework designed to accelerate decision cycles by prioritizing mission-critical computations based on factors such as relevance, urgency, risk, information gain, confidence, and resource cost.

- A trust quarantine architecture featuring trust scoring, peer-consistency checks, anomaly detection, re-attestation workflows, audit trails, and human notification processes to ensure network node integrity.

- Human-in-command governance mechanisms that enforce policy-based approval workflows, preserving human authority over consequential actions while enabling autonomous execution within predefined parameters.

- The Cube™ hardware root of trust, a compact secure hardware module embedding encrypted software and firmware, biometric authentication, cryptographic processing, secure memory, secure boot validation, hardware random number generation, and tamper detection.

- Degraded-mode resilience protocols to maintain operational continuity during node loss, communication degradation, or system faults.

Danny Rittman, Inventor and Chief Technology Architect of SDNN™, emphasized the innovation’s significance: "SDNN™ represents a fundamental rethinking of how AI can coordinate distributed intelligent systems. Rather than relying on isolated point solutions operating independently, SDNN™ is being designed with the goal of serving as a unified intelligence layer that can fuse information, reason across an operational picture, coordinate networked nodes, and learn from each mission cycle—while preserving human authority over consequential decisions."

In addition to the provisional patent application, VisionWave has filed a U.S. trademark application for SDNN™ as part of its broader intellectual property strategy to protect the brand identity associated with its emerging AI architecture. The trademark application is currently under examination by the United States Patent and Trademark Office (USPTO), with registration not yet guaranteed.

The filing comes amid a rapidly expanding autonomous systems market. According to 6Wresearch internal data and industry insights, the market was valued at approximately USD 22.6 billion in 2025 and is projected to grow to USD 61.3 billion by 2032, reflecting a compound annual growth rate (CAGR) of 14.2% from 2026 to 2032. This growth is driven by increased automation adoption in defense, transportation, and industrial sectors, rising demand for unmanned vehicles and drones, advancements in AI and machine learning, and a growing focus on operational efficiency, safety, and precision.

VisionWave’s SDNN™ architecture aims to address these market demands by providing an advanced AI framework capable of multi-domain command-and-control and intelligent system coordination, potentially positioning the company at the forefront of AI-driven autonomous system innovation.