VisionWave Files RF Fire Control Patent, Lands First Drone Order and $60M xClibre IP

VWAVVWAV

VisionWave filed a U.S. patent application for its AI-Assisted Multi-Modal RF Fire Control System and acquired 100% of the xClibre™ AI video intelligence IP portfolio valued at ~$60 million. It also secured its first commercial drone systems order from a Latin American public safety agency and signed a $17.5 million term sheet to invest in Foresight Autonomous.

1. Strategic Transactions and Patent Filing

On April 20, VisionWave filed a non-provisional U.S. patent application (Serial No. 19/652,090) for its AI-Assisted Multi-Modal RF Fire Control System, claiming priority from an October 2025 provisional filing. On April 10, the company completed the acquisition of 100% of the xClibre™ AI video intelligence IP portfolio—independently valued at ~$60 million—through issuance of 7 million shares and a $6 million promissory note.

2. First Commercial Revenue Booking

On April 2, VisionWave received its first signed purchase order from a Latin American public safety organization for drone-based operational systems and integrated payload technologies, marking its transition from demonstration engagements to initial commercial revenue generation in the homeland security sector.

3. Proposed Investment in Foresight Autonomous

On April 21, VisionWave signed a non-binding term sheet to acquire up to 51% of Foresight Autonomous for $17.5 million in VisionWave equity, priced on a five-day average VWAP. The transaction, subject to due diligence, regulatory and shareholder approvals, targets a definitive agreement within 30 days and closing within 45 days thereafter.

4. Platform Architecture Evolution

With the xClibre acquisition and proposed Foresight investment, VisionWave has expanded its sensing platform into a four-layer architecture combining RF detection (VisionRF™), stereo/thermal computer vision (Foresight), AI video analytics (xClibre™) and autonomous command-and-control pipelines, designed to reduce false-positives and accelerate detection-to-decision timelines.

Sources

F