ZaiNar, the Foundation Layer of Physical AI, valued at $1B+ and $100M investment

BELMONT, Calif. February 19, 2026. ZaiNar today emerged from nine years of stealth with a breakthrough platform for Physical AI, tech that turns any wireless network into a sensing system that continuously knows where everything is, without satellites, cameras, or drain on device power or compute. The company has had more than $100M in investment and a valuation exceeding $1 billion. Andreas Weigend is a ZaiNar Advisor (former Chief Scientist at Amazon), and investors include Steve Jurvetson (ZaiNar and SpaceX Board member), Jerry Yang (founding partner, AME Cloud Ventures and co-founder, Yahoo!), Tom Gruber (co-founder of Siri), Jaan Tallinn (founding engineer of Skype and co-founder of Metaplanet Holdings), and Nicholas Pritzker (co-founder of Tao Capital).

Expected to be one of the largest technology markets ever created, Physical AI is intelligent machines that move and work by themselves, at endless scale, in the real world. Until now, AI has lacked the right kind of data to train itself and to move reliably in the physical world, i.e., centralized, real-time location information that is accurate to the sub-meter and synchronized continuously.

“Physical AI needs a live, continuous feed of where everything is, and that dataset simply did not exist. By solving time synchronization at the sub-nanosecond level, we’ve turned existing infrastructure into the foundation layer for Physical AI. This funding accelerates deployment with carrier and enterprise partners globally.”

“ZaiNar has solved a problem that’s stymied the industry for decades,” said Steve Jurvetson, Board Member, ZaiNar; Board Member, SpaceX. “Precise positioning without dedicated hardware infrastructure opens markets that were previously inaccessible.”

"ZaiNar is building essential infrastructure for the next computing paradigm,” said Jerry Yang, founding partner, AME Cloud Ventures, and co-founder, Yahoo!

“Whether in a hospital, on a construction site, or in a fulfillment center, knowing precisely where things are is crucial for making good decisions,” said Dr. Andreas Weigend, former Chief Scientist at Amazon. “I wish something like ZaiNar had existed when I was at Amazon: Not only would it have changed how we operated, but also where we set the bar.”

ZaiNar’s Innovation

ZaiNar solves the problem with existing wireless infrastructure and signals (the radio waves already broadcast by every device, everywhere). It can time-synchronize these signals a thousand times more accurately than conventional network time synchronization, and so derive vastly superior positioning information.

Radio waves travel at approximately 30 centimeters per nanosecond. This rate of travel, essentially constant, means that sub-nanosecond synchronization translates directly into sub-meter positioning accuracy, even indoors, outdoors, through walls, and around corners.

ZaiNar’s breakthrough changes how 5G and IoT networks can be used, turning them into sensing platforms that can take on the burden of location processing, allowing new levels of device and edge coordination. Every connected device on a network will know where it is in relation to other objects with sub-meter accuracy, in real time.

Why Existing Location Sensing Can’t Help AI Get Physical

GPS, cameras, and beacons are powerful tools, but none of them offer the low-power, low-compute, and continuous accuracy needed for Physical AI training and inference. GPS is highly accurate and forms a foundation for all modern navigation and location, across every industry, including defense, aerospace, and military applications. But its most common use cases don’t offer sub-meter accuracy, and by and large, it cannot function well indoors, underground, or in dense urban environments. Cameras and computer vision require a visual line of sight and drift, or accumulate small errors that compound into large ones, unless more and more processing and power are used to keep machines located. Ultra-wideband beacons require covering every environment with proprietary hardware costing thousands of dollars per facility, weeks of installation, and custom calibration that breaks when you rearrange the shelves.

ZaiNar works with the 5G and WiFi infrastructure and signals already deployed and transmitting worldwide, with no added hardware or software. This transforms sunk costs into new capabilities.

Deployed and Operating Today

ZaiNar is deployed and operating today, freeing construction workers from hazard zones, helping healthcare teams find medical devices, and enabling coordinated autonomous operations across industries. It turns out the spatial awareness layer Physical AI needs doesn’t require next-gen 6G networks or legions of robots. It runs on tech we have now, producing capabilities we thought were further in the future.

Intellectual Property and Commercial Momentum

ZaiNar has filed more than 100 patents and has been issued 90 with zero rejections, covering its core functionality in phase-based time synchronization and network-computed positioning. A 100% IP allowance rate is a statistical anomaly in a field as mature as radio frequency engineering, confirming the innovative, original nature of ZaiNar’s insights and their applicability.

The technology is protocol-agnostic and works across 5G, WiFi, private cellular networks, and future wireless standards.

The company has secured more than $450 million in contracts and memoranda of understanding and is deployed commercially across healthcare, construction, smart city, and industrial applications on multiple continents, with major carrier and enterprise partnerships to be announced in the coming weeks.

Beyond Positioning

Sub-nanosecond synchronization has implications far beyond knowing where things are. Data centers send packets with buffer gaps to prevent collisions, like cars leaving following distance on a highway. ZaiNar’s synchronization could shrink those buffers dramatically, potentially doubling throughput without additional bandwidth or power. Defense applications depend on GPS, which can be jammed or spoofed, while ZaiNar’s approach uses existing cellular and WiFi signals that can’t be fooled the same way, and so creates immediately-available terrestrial backup for GPS.

The smarter use of connectivity signals is all that’s needed to unlock a physical future for AI, today.