Custom edge AI development
Neural models compiled for the silicon they run on, within strict power budgets.
NXP i.MX · Silicon Labs EFR32 · NVIDIA Jetson
Real-time intelligence on factory lines, sensors and embedded devices. We quantize, compile and validate networks directly for your target accelerator, sub-20ms inside 2W–15W envelopes, with zero cloud dependency.
What you get
- A compiled model for your exact silicon target
- Latency and power report measured on-device
- 60fps vision or sub-milliwatt acoustic pipelines
- On-device evaluation harness
How it works
- 01 · Profile the task and select the accelerator
- 02 · Design or compress the network to the power budget
- 03 · Compile with vendor toolchains (eIQ, JetPack, vendor SDKs)
- 04 · Validate latency, accuracy and thermals on hardware
Good fit if
- Cloud round-trips are too slow or too costly
- Devices run on battery or harvested power
- Connectivity cannot be assumed
Deploy custom AI on your terms.
Tell us about your target silicon, data residency constraints, or latency requirements. Rochon engineers will provide a clear evaluation of what is viable, with power and latency models and deployment blueprints.