The thesis
Every serious system eventually meets the same wall: the answer arrives after the moment it was needed. Edge AI is not a smaller cloud. It is a different assumption about where the thinking happens.
Four reasons, no mysticism
01 / LATENCY
A round trip to a datacenter and back is a tax you pay on every single event, and it is charged in the currency your customer notices most: the pause before something happens. A gate that opens a beat late feels broken even when it is working perfectly.
02 / PRIVACY
Audio and video are the two data types people care about most and regulators ask about first. Process them on the device and the difficult conversation disappears — not because you promised, but because the data never left the building.
03 / CONTINUITY
Construction crews cut fibre. Storms take out cells. A security product that stops securing when the internet hiccups is not a security product, it is a subscription. Local intelligence degrades gracefully instead of going quiet.
04 / UNIT ECONOMICS
Cloud inference bills you forever, per event, per device, per customer — and scales exactly as fast as your success does. Silicon in the product is capex you spend once, at a price you negotiated, in a currency you control.
The cloud is wonderful at remembering, comparing and training. It is terrible at reacting. So we stopped asking it to.
Be honest about it
We would rather lose the project than sell you silicon you do not need. Some problems genuinely belong upstairs.
TRAINING
Models are trained where the GPUs are. That is a cloud or a workstation job, and pretending otherwise is expensive theatre. The edge runs the result.
FLEET MEMORY
Cross-site analytics, long history, fleet-wide search: these want a database with a view of everything. Keep them central, and keep the reflex local.
RARE + HUGE
If a task runs twice a month and needs a frontier model, rent it by the minute. Paying for that capability in every unit you ship is how a good margin quietly dies.
How we split it
Every system we build draws this line explicitly, on purpose, on the first day — because the products that age badly are the ones where it was drawn by accident.
ON DEVICE
Wake word, speech, detection, classification, sensor fusion, the safety interlock, the response that must not wait for anyone's permission.
ON PREMISE
A hub or small box holding the household or site model, orchestrating devices, keeping recent history, serving the apps on the local network.
IN CLOUD
Identity, provisioning, fleet telemetry, long history, model training and the update channel that carries the next model down to the edge.
The test
That is the whole question. Bring us the answer you are least happy with and we will tell you, in two weeks, what it takes to move the intelligence into the room.