British defense company OpenWorks Engineering has been selected to supply its Vision Guard intelligent optics system for evaluation under the Australian Defence Force's Project Land 156, a counter-drone modernization program valued at AU$1.3 billion (Interesting Engineering; The Defense News). Vision Guard is a backpack-portable early-warning platform combining panoramic surveillance with AI-driven drone detection and sensor fusion. The system supports modular sensor configurations including radar and acoustic arrays, integrates via ATAK, SAPIENT, and Cursor on Target protocols, and can classify Class 1 unmanned aerial systems. It deploys in under two minutes. Leidos Australia serves as the program's systems integration partner. Land 156 uses rolling contracts and continuous evaluations, with more than 120 technologies assessed to date. OpenWorks, also known for its SkyWall drone-capture systems, reports Vision Guard is already in service across Europe and the United States and participated in the joint U.S.-U.K. Project Vanaheim exercise in Germany.
What happened
British defense technology company OpenWorks Engineering has been selected to supply its Vision Guard intelligent optics system for evaluation under the Australian Defence Force's (ADF) Project Land 156, a counter-drone modernization program valued at AU$1.3 billion (Interesting Engineering; The Defense News, June 17 2026). Leidos Australia serves as the program's systems integration partner, tasked with developing a layered, distributed counter-UAS architecture. Land 156 uses rolling contracts, continuous demonstrations, and ongoing technology assessments; more than 120 drone detection and defeat technologies have been assessed through the program to date.
Technical details
Vision Guard is OpenWorks Engineering's smallest and lightest intelligent optics platform, developed specifically for dismounted infantry. It provides a panoramic staring capability - continuously monitoring a wide area without requiring manual operator scanning - and applies AI-driven data fusion software to detect, track, and classify Class 1 unmanned aerial systems at extended ranges. The system supports modular sensor configurations integrating active and passive detectors, including radar systems and acoustic panels, and communicates through established military protocols including ATAK (Android Team Awareness Kit), SAPIENT, and Cursor on Target (COT). Core equipment fits in a standard military backpack and can be deployed in under two minutes. The system is also optimized for low-light and covert observation environments.
Operational track record
OpenWorks, also known for its SkyWall net-capture drone defeat systems, reports Vision Guard is already in service with customers in Europe and the United States. The system participated in Project Vanaheim in Germany, a joint U.S.-U.K. counter-drone interoperability exercise, where it was deployed at the platoon level against simulated drone threats.
Evaluation context
Selection for Land 156 evaluation does not guarantee a production contract. Vision Guard competes alongside other detection and defeat technologies as the ADF refines its future C-UAS requirements. For practitioners building edge AI and sensor-fusion systems, the push toward portable, low-power detection kits highlights design tradeoffs between weight, power budget, and on-device inference latency when moving detection stacks to the tactical edge. Lightweight sensor-fusion platforms that maintain low false-positive rates while operating under strict SWaP (Size, Weight, and Power) constraints are increasingly seen as essential for frontline infantry in drone-contested environments.
Scoring Rationale #
Corroborated by The Defense News and confirmed via OpenWorks operational details (Project Vanaheim, ATAK/SAPIENT/COT integration). Story matters to practitioners building edge AI and sensor-fusion systems but is primarily a military procurement evaluation, not a frontier AI release. The contract scale and Leidos integration role give it practitioner relevance for low-SWaP, low-latency inference design.
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