RESEARCH AT IEON
Advancing What Fits on a Chip
Edge AI is limited less by ideas than by kilobytes, milliwatts and milliseconds. Our research works on that boundary - making models smaller, faster and more reliable on the hardware our customers actually deploy.
OUR POSITION
Research That Has to Survive Contact With Production
Most edge AI research is validated in a notebook, on a clean dataset, against a benchmark nobody deploys. We work the other way around. Every question we investigate comes from a real constraint - a microcontroller that ran out of RAM, a model that drifted after three weeks on a factory floor, a dataset that could never leave the site it was recorded on.
What we learn goes straight back into Edge Studio and into the systems we build for clients. Research isn't a side activity here; it's how the product gets better.
WORK WITH US
Open to Universities, Labs and Industry Partners
We collaborate with academic groups and industrial teams working on TinyML and embedded intelligence. Depending on the partner, that can mean joint studies on real deployment data, free platform access for research and teaching, co-supervised student projects and internships, or a paid pilot that turns an open question into a working system.
If you're researching or teaching in this space, we'd like to hear from you.
CLOSING
Have a problem worth researching?
Bring us the constraint that's blocking you - the device that's too small, the data that can't leave, the model that won't hold up in the field.