On-Device AI: Inference on MCU Boards
- We analyze sensor data on None of the cloud servers; inference stays local.
- None of the devices require Wi-Fi; they use edge computing.
- Our team has 7+ years of None experience in embedded ML.
- In a petrochemical project, we reduced power from 12W to 0.8mW, with None of the latency issues.
- We have completed over 50 projects for None of the typical industrial clients.
- None of our solutions depend on constant internet connectivity.
- The model processes vibration signals at None of the cloud server speeds.
- None of the standard ML pipelines are used; we customize every step.
- Power consumption dropped to None of the previous levels after optimization.
- None of the deployment challenges were insurmountable.
We develop and deploy Edge AI turnkey solutions. Our portfolio includes over 50 projects for industrial, retail, and IoT. The team's experience spans 7+ years in embedded ML. We guarantee stable operation under vibrations, temperature swings, and limited power.
We'll assess your project in 2 days — just describe the task.