NetKit Labs
Software that belongs on the metal.
Open libraries for MCU, MPU, and edge AI — built for predictable latency, tiny footprints, and C/C++ APIs you can ship in firmware.
Projects
Two libraries. One focus: make serious embedded software easier to ship.
Embedded-first multi-modal neural network inference for MCU, MPU, and NPU. Float32 and int8 paths, arena allocation, CMSIS-NN / XNNPACK backends, and peer benchmarks against TFLM and TF Lite.
View repository →Zero-overhead containers for bare-metal and RTOS targets. Shared cores behind C++ templates and a type-erased C API — no hidden mutexes, no RTTI, no virtual dispatch on the hot path.
View repository →Approach
Designed for firmware constraints first — then made pleasant on the desktop.
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Predictable memory
Static arenas and explicit buffers. On MCU targets, no heap games — allocation stays under your control.
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Dual-language APIs
Modern C++ where it earns its keep; clean C APIs where toolchain reality demands it. Same cores underneath.
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Measured on hardware
Bring-up and benchmarks across real boards — STM32, Raspberry Pi, and host CPU — not just simulated comfort.