From research model to FPGA, faster.
Training, tools and hands on support for universities and research labs deploying machine learning on FPGAs and edge hardware.
Training, tools and hands on support for universities and research labs deploying machine learning on FPGAs and edge hardware.
Three ways to shorten the path from a trained model to working hardware in your lab.
Institutional workshops and courses tailored to your hardware and research goals. Your researchers and students go from compression theory to a model running on an FPGA.
TrainingOne platform from dataset to FPGA firmware, built on open source hls4ml. Academic licenses available for courses and research labs.
PlatformHands on support for your project: model optimization, FPGA deployment and reproducible workflows. We also join funded research proposals as a technical partner.
ProjectsInstructor in international schools on FPGA, SoC and embedded AI at ICTP since 2019, and tutorial author at FastML 2026.
Our workflows build on hls4ml and QKeras, the tools already trusted by the scientific instrumentation community. No lock in.
Training, compression, HLS conversion and deployment on Zynq SoCs. One team that understands both the model and the hardware.
Insights, tutorials, and updates on ML, FPGAs, and hardware acceleration.
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