Khalid
Khalid is an edge-AI reconnaissance and target-tracking solution that interfaces with IR and visible-light camera arrays while reducing operator workload, radio exposure, and susceptibility to jamming.
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Khalid, a name associated with endurance and longevity, is designed as a resilient edge-AI system for reconnaissance and target tracking in contested environments. Its architecture moves recognition and tracking tasks closer to the device or drone itself, reducing dependence on constant operator intervention.
The system can interface directly with infrared (IR) and visible-light (VIS) camera arrays and operate in idle or edge modes depending on mission needs. Communication with the operator can be limited to sending processed data or requesting approval for decisions, helping reduce communication load while preserving operational control.
By shifting target recognition responsibility from the operator to the platform, Khalid supports more autonomous field performance, extends radio silence, and improves resistance to jamming. It is designed to support real-time terrain-based target and location tracking in military reconnaissance workflows.
Many current solutions rely heavily on software-side signal processing, which can introduce meaningful delays in real-time response. Khalid addresses that limitation by performing more of the decision-making and recognition pipeline closer to the edge, improving responsiveness and operational efficiency.