Vision
Detection, classification, and inspection running at frame rate on the camera itself.
Services · Edge AI
Edge AI Integration
Intelligence inside the budget you have.
Edge hardware gives you a fixed amount of memory, power, and time. We fit the model to it and wire it into the runtime on the device: language models, vision, anomaly detection, and the control models you already run.
What you get
It runs on the device.
Work that stays on the hardware answers in milliseconds, keeps running when the link drops, and sends nobody's data anywhere. We make the model small enough and fast enough for that to be true on the hardware you ship.
You get a model that fits the silicon you have chosen, integrated into your application, with the accuracy cost of every compression step measured rather than assumed.
The work
Fitting the model to the metal.
- Sizing. Model selection and compression against your memory, power, and thermal budget, before anyone writes integration code.
- Quantization and pruning. Taken as far as the accuracy checks allow, with the tradeoff written down at each step.
- Runtime and accelerator. The right runtime for the silicon you have, and the integration into the application that uses it.
- Latency engineering. Tuned to the response time your product actually needs, measured on the device rather than on a workstation.
- On-device pipelines. Preprocessing, batching, and sensible behavior when the input goes strange or the sensor lies.
- Field updates. Getting a new model onto deployed units safely, with a way back if it misbehaves.
Both kinds of model
Language models and classical ML.
A vision model on a camera, an anomaly detector on an industrial controller, a control model in a vehicle, and a language model on a handheld are the same engineering problem: a fixed budget, a required response time, and no room for a round trip to a datacenter. We work across all of them.
Signals
Anomaly detection and control models on instruments and industrial hardware.
Language
Compact language models on handhelds and embedded systems, with no connection assumed.
Where it runs
Robots, vehicles, instruments, and sites with no signal.
Factory floors, field instruments, handhelds, aircraft, and anything that has to keep working when the network does not. If the hardware is already chosen, we fit the model to it. If it is not, we will tell you what the workload needs before you commit to the part.
The job is done when it hits the response time on the device you ship, not on a test bench.
Tell us the device and the budget.
Send us the hardware, the model, and the response time you need out of it. We will tell you what fits.
Talk to an engineer