Capabilities
Edge AI & embedded intelligence
Inference that runs on the device — on a microcontroller, an SoC or an FPGA — with a power and latency budget that holds.
Intelligence is moving into the device. Not because the cloud stopped working, but because a machine that has to react in two milliseconds, keep running when the link drops, and not send its images anywhere cannot wait for a round trip.
What this actually involves
Putting a model on an embedded target is an engineering problem long before it is a data-science one. The model has to fit in flash. The inference has to finish inside the control loop. The sensor data has to arrive conditioned and time-stamped. The board has to dissipate the heat of running inference continuously, in an enclosure, in a factory, in August.
We do that work end to end: choosing the target, sizing and quantising the model, designing the hardware around its real power and memory draw, writing the pipeline that feeds it, and measuring the result on hardware rather than in a notebook.
Where the inference runs
On a microcontroller when the problem is small, the power budget is tight and the answer is a classification or an anomaly score — vibration monitoring, audio event detection, predictive maintenance.
On an application SoC or NPU when there is a camera, a screen or several models running at once, and embedded Linux is already in the design.
On an FPGA when the data rate is the constraint: line-scan cameras, multi-sensor pipelines, or a decision that has to be made deterministically in microseconds rather than “usually fast enough”.
Choosing between those three honestly — including saying that a plain signal processing algorithm would beat a neural network here — is part of the job.
Honest about the limits
An embedded model is only as good as the data it was trained on and the sensor that feeds it. We would rather spend the first weeks of a project instrumenting your machine and collecting real data than shipping a demo that works on the dataset and fails on the factory floor.
Get in touch
Build your next intelligent product with DeeplyDynamics.
Tell us what you are building and what is in the way — the timing, the noise, the power budget, the deadline. We will tell you honestly whether we are the right people for it, and what we would do first.