Bandwidth & threat surface
Continuous 1080p streaming saturated site links and exposed feeds to interception.
Lekuko IoT · Edge AI & Embedded
Hardware-adjacent AI and real-time machine vision process at the point of capture. No cloud latency, recurring compute dependency, or external raw-video pipeline.
Edge intelligence // Engineering mandate
Cloud platforms fail industrial workloads when network round trips, bandwidth limits, and data residency requirements conflict with real-time operations. Lekuko moves inference beside the sensor and returns only the operational result.
The hardware pipeline progresses from rapid Raspberry Pi prototypes to Nvidia Jetson tensor processing, industrial System-on-Modules, and custom PCBs. OpenCV, PyTorch and TensorRT are optimized around real environmental and compute limits.
Architectural stack | Capability matrix
Scope, materials and response targets shaped around each deployment's physical and operational constraints.
Continuous 1080p streaming saturated site links and exposed feeds to interception.
Cloud round trips delayed gate actuation and added escalating compute charges.
Retention had to remain local while small operational events reached client systems.
Micro-defects on belts moving faster than human inspection can follow.
Shifting factory lighting made fixed-threshold vision prone to false positives.
Faults had to be rejected physically without slowing the line.
Terminal routing | B2B intake
If cloud latency, bandwidth, industrial friction or sovereignty requirements constrain operations, submit your technical parameters for evaluation by our edge engineering team.
Initiate technical briefing