5G’s Killer App Has Arrived: Highly Accurate Location without GPS

ZaiNar bypasses handset gatekeepers to give carriers and enterprises direct control of 5G positioning for the first time, turning 5G networks into Physical AI infrastructure.

No device software, no OEM cooperation, no satellites required.

BELMONT, Calif., Feb. 27, 2026 /PRNewswire/ — ZaiNar today announced commercial availability of its 5G positioning technology, the first 5G location system that operates entirely independent of device makers, using the network as a sensor (i.e., connectivity signals that devices already transmit) to deliver sub-10cm accuracy at ranges up to 1.5km. The network-side solution achieves sub-10cm accuracy using only existing connectivity signals, requiring no software on user devices, no dedicated positioning hardware, and consuming zero additional battery. Operating on as little as 10 MHz of spectrum, ZaiNar is the only 5G positioning system that works on bandwidth-constrained private 5G and low-power 5G IoT networks, the environments where location services can be worth more than the connectivity itself.

“5G’s killer app has finally arrived, and it’s not theory, it’s deployed,” said Daniel Jacker, CEO and Co-Founder of ZaiNar. “We’re proving sub-10cm accuracy in real-world deployments across healthcare, construction, logistics, and smart city applications. This technology turns 5G from a faster pipe into genuine infrastructure for Physical AI.”

“ZaiNar’s submeter location is the unlock for Physical AI. It brings forward telcos as a key piece of the Physical AI ecosystem by providing the missing data layer, both for real-time coordination and training grounded in real-world 2D and 3D vectors. The enterprise applications span traffic management, advertising, logistics, and healthcare. ZaiNar’s solution outperforms alternatives and works across both WiFi and 5G, including wide-area carrier networks and private deployments. Due to the size of the opportunity, I have joined as a board advisor,” said Nishant Batra, Board Advisor, ZaiNar; Former CTO, Nokia.

A New Utility for 5G

Unlike conventional approaches that rely on dedicated positioning reference signals (PRS or PSRS), ZaiNar’s patented technology uses the connectivity signals (SRS) that every device already transmits. PRS and PSRS signals can only be sent once per second, limiting them to stationary use cases. SRS signals are transmitted 100 to 500 times per second, enabling ZaiNar to track fast-moving objects, such as vehicles, drones, robots, mobile workers, in real time.

Today, mobile operating systems made by Apple and Google determine whether a device shares its positioning signals with the network. In practice, both deny PRS and PSRS requests by default, granting access only where legally required, such as E911 emergency services. This means carriers have invested billions in 5G infrastructure but cannot offer location services on the handsets connected to their own networks.

ZaiNar’s SRS-based approach changes this equation entirely. Because SRS is a connectivity signal, the device must transmit it to maintain its network connection — positioning becomes a network function, not a handset function. Carriers and enterprises gain direct access to sub-10cm location data on every phone, robot, car, or IoT device, with no dependence on operating system permissions, app-level access, or device manufacturer cooperation. In terms of power, compute, and security, this shift from device-side to network-side positioning represents a significant improvement in 5G utility.

Proven Performance

ZaiNar has demonstrated sub-10cm accuracy on CBRS Band 48 networks with just 20MHz bandwidth. Additional proven capabilities include 1.5km read range and zero additional battery drain on tracked devices. ZaiNar is not only the best positioning method across 5G cellular, it’s the best location service across any modality, including GPS RTK, Ultra-wideband (UWB), WiFi, Bluetooth, and RFID.

Why It Matters

The telecommunications industry has invested heavily in 5G infrastructure globally, yet super-accurate indoor and outdoor positioning (long promised as a key 5G capability) has remained elusive. GPS fails indoors. Existing 5G positioning delivers meter-level accuracy at best. WiFi positioning is limited to a range of tens of meters. Cameras need line of sight. Beacons can’t adapt to fast-changing environments. All suffer from latency.

ZaiNar changes this equation. Using radio waves that phones, cars, drones, robots, and IoT devices everywhere already emit, ZaiNar’s engineers achieved sub-nanosecond time synchronization and distribution. Because radio waves travel consistently at ~30 centimeters per nanosecond, ZaiNar can derive centimeter-level positioning for anything connected to the network, extracting positioning data from signals the network already uses for connectivity, without new hardware, software, or battery drain.

What is Physical AI?

Physical AI is artificial intelligence that operates in the physical world, rather than behind a computer screen. Just as digital AI required the internet’s data to work well at scale, physical AI requires continuous, hyper-accurate data on where everything is, for both AI training and AI coordination of movement in three-dimensional space.

This has been Physical AI’s challenge: unlocking its potential requires sub-meter accuracy and real-time awareness across all connected devices, within tight power, compute, and latency constraints. In practice, this means no added hardware or software on the device. ZaiNar meets this challenge and solves for all of these requirements.

5G Networks as Physical AI Infrastructure

With ZaiNar, 5G networks become spatial infrastructure for Physical AI. ZaiNar enables AI RAN capabilities that integrate artificial intelligence and location sensing directly into 5G, turning the entire network into a sensing platform that provides its users with always-on, real-time spatial context, which is a significant gain in network value and utility.

In robotics, ZaiNar’s technology supports a level of autonomous machine navigation that far exceeds what’s possible with GPS or cameras. It offers sub-meter accuracy even indoors and outside line of sight. Today, to operate indoors, robots mostly rely on cameras and SLAM (simultaneous localization and mapping). This only tells the robot what it can see. And the longer a machine operates and the farther it travels, the more memory, compute, and power it consumes (not on its primary task, but just to know where it is and to resist location drift).

ZaiNar’s technology allows robots to offload that resource-intensive compute to the 5G network, freeing onboard processing for higher-level tasks while providing a more efficient, continuous, real-time sensing and location feed. With this new level of spatial utility, 5G doesn’t just keep a robot informed about where it is. The network can also inform the robot in real time where all other robots, workers, and equipment are. This unlocks swarm intelligence and autonomous coordination at scale.

Commercial Momentum

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

About ZaiNar

ZaiNar is the foundation layer of Physical AI. The company’s patented technology achieves sub-nanosecond time synchronization and distribution across wireless networks, transforming existing 5G and WiFi infrastructure into a comprehensive spatial sensing system. ZaiNar delivers central spatial awareness so connected systems know their location, understand surrounding assets, and share that context with AI that coordinates the physical world. Founded in 2017 and headquartered in Belmont, CA, the company has had over $100 million in investment, is backed by tier-1 investors, including sharing a board member with SpaceX, and is valued at more than $1 billion. For more information, visit zainartech.com.

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SOURCE ZaiNar, Inc