Limited onboard processing (driven by SWaP constraints) leads to lag, dropped detail, and slower system response in live conditions.
Low light, low contrast, and occlusion make targets hard to distinguish, increasing misidentification risk, including friendly fire.
Interfaces are slow and fragmented, forcing operators to interpret multiple inputs instead of receiving clear, real-time information in one view.
Detection, confirmation, and action are sequential and manual, increasing response time and exposure during operations.
FPGA pre-processes imagery, AI feeds back for overlays, with dynamic power and thermal control.
On-device learning from operator corrections to improve performance.
Real-time firing solution that accounts for range, wind, angle, and atmospheric conditions.
Human, vehicle, and threat classification with confidence scoring for real-time assessment.
Kalman-filtered auto-tracking that maintains lock through motion and occlusion.
CNN-based target detection trained on military datasets for consistent identification across conditions.
Designed for mobile units operating in dynamic environments, enabling rapid detection and engagement with minimal delay.
Supports precision targeting with real-time ballistics, tracking, and stable target identification at range.
Enables continuous monitoring and threat detection across static surveillance posts and perimeter deployments.
FX-EDGE is co-developed with established defence partner RRP S4E Innovations, combining FieldX’s edge intelligence with proven manufacturing scale, certified infrastructure, and operational experience.
This partnership enables production-ready systems aligned with defense standards, sustainment requirements, and real field conditions.
