LEVCOM builds deterministic edge AI systems for robotics, industrial vision, and autonomous platforms — combining FPGA acceleration with modern AI frameworks where GPU-only solutions fall short.
Our stack spans FPGA fabric to AI runtime. Every layer is tuned for one outcome: bounded latency under real-world conditions, with the power profile of dedicated silicon.
Production-grade inference pipelines on AMD/Xilinx platforms. Custom dataflow architectures purpose-built for the model and the sensor.
Image and signal preprocessing fused with inference. Sensor-to-decision in a single deterministic dataflow — no PCIe round-trips.
INT8 quantization, kernel fusion, and topology-aware mapping. Optimized for the smallest model footprint that meets the spec.
DMA, AXI streams, DDR bandwidth optimization. Zero-copy paths between sensor, fabric, and compute — where bottlenecks actually live.
Four stages. One dataflow. No surprises. The pipeline is designed so each stage has a known execution budget — performance you can put in a spec sheet.
MIPI-CSI, GMSL, GigE Vision. Raw input enters the fabric.
Debayer, color correction, ROI extraction. Streamed, not buffered.
Hybrid FPGA + GPU execution. The right substrate for each operator.
Robotics, control loops, industrial systems. Closed-loop ready.
Edge deployments where missing a deadline is a failure — not a slow frame.
// navigation + grasp planning at control-loop rates
// defect detection on the line, not in the cloud
// integrated AI imaging, sub-watt active power
// drones, UGVs, mobile platforms with hard real-time budgets
We work with early design partners on robotics, industrial vision, and autonomous-system programs where deterministic latency is a hard requirement.
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