The Spatial Awareness Layer for Physical AI
Deeyook turns the Wi-Fi signals already in the air into sub-meter spatial understanding — indoors and out, with or without GPS, and with no new hardware. The grounding layer every AI system needs to act in the physical world.
From location to context, from signals to intelligence.
Spatial Awareness, Built Into the Device
A native sense of place for wearables, XR glasses, cameras, and handhelds — added as firmware on the Wi-Fi silicon already inside them.
he next generation of devices is expected to understand where it is — not with a bolted-on module or a separate network, but as a native capability. Deeyook makes spatial awareness a platform primitive: firmware on the commercial Wi-Fi silicon a device already ships with, turning it into a sub-meter-accurate spatial sensor with no added bill of materials. For device-makers, that's a new capability with zero new hardware.
A platform primitive, not an accessory
Spatial awareness becomes part of what the device is — available to every app and agent on it, the way a compass or accelerometer is. Delivered in firmware, it ships to the entire installed base through software.
XR and smart glasses
Spatial computing needs to know where the wearer is, continuously and indoors, to anchor content to the world. Deeyook provides that grounding from the device's own Wi-Fi radio — no external trackers, no room setup.
Body-worn cameras & handhelds
Field devices gain precise, automatic location context indoors, where GPS drops — adding spatial meaning to what they capture, with no separate positioning system to deploy.
Zero added hardware
Because it's firmware on silicon that's already there, spatial awareness costs no new components and no supply-chain change. Integrate once; scale to millions of units.
Ubiquitous
Continuous positioning indoors, underground, and through the GPS shadow.
Sub-meter precision
Continuous accuracy at the resolution autonomous systems need to act.
Scalable
Rides the Wi-Fi access points already deployed. No build-out.
Self-learning
Adapts automatically to changing RF environments. No calibration.
Efficient
Minimal power consumption ensures long-lasting operation.
Firmware, not hardware
Ships as software into existing silicon. Scales to millions.