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ZaiNar Raises $100M, Uses Wireless Networks for AI Sensing

Highlights

  • ZaiNar secured $100M to advance its physical AI platform deployment.

  • The technology uses current wireless networks to deliver location data.

  • Protocol-agnostic design enables application across many industries worldwide.

Kaan Demirel
Last updated: 24 February, 2026 - 8:20 pm 8:20 pm
Kaan Demirel 4 hours ago
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Emerging from nearly a decade in stealth, ZaiNar announced a major funding milestone and the release of its physical AI platform intended to shift how wireless networks are used for location awareness. The Silicon Valley-based company aims to turn conventional 5G, Wi-Fi, and IoT networks into large-scale real-time sensing systems, aiming to address the industry-wide challenge of acquiring accurate location data without relying on satellites or cameras. With widespread enterprise adoption as a goal, ZaiNar is betting on its approach to create more intelligence and coordination among connected devices across a variety of sectors, from healthcare to industrial operations.

Contents
Why do traditional location tools fall short for physical AI?How does ZaiNar use wireless signals to achieve high accuracy?What advantages has ZaiNar secured with its technology and partnerships?

Reports from past years about ZaiNar’s quiet technology development described the company as working on localization and synchronization for wireless networks but provided only minimal public details. Until now, their efforts focused on theoretical applications and smaller pilot projects. This week’s announcements contrast sharply with previous information, demonstrating that ZaiNar has attracted prominent deep-tech investors, expanded IP protection, and secured commercial contracts on several continents, signifying its transition from stealth project to active deployment.

Why do traditional location tools fall short for physical AI?

Physical AI applications require real-time, accurate positioning in diverse environments. ZaiNar identifies that GPS, cameras, and beacons each fall short in reliability and scalability, whether it’s limited precision indoors, visual obstructions, or complex setup and calibration demands. These gaps have left industries seeking a robust alternative capable of delivering precise location intelligence without excessive infrastructure or power consumption.

How does ZaiNar use wireless signals to achieve high accuracy?

The company’s platform operates by synchronizing existing wireless signals to sub-nanosecond accuracy, allowing for sub-meter location determination in challenging indoor and outdoor conditions. This method leverages the fixed speed of radio waves, enabling devices to continuously locate themselves and one another in real time. According to ZaiNar, its technology does not require additional hardware, making deployment faster and more scalable across different network protocols.

What advantages has ZaiNar secured with its technology and partnerships?

ZaiNar has built an extensive patent portfolio, protecting innovations in phase-based synchronization and network-computed positioning. Its platform, which works across multiple wireless standards, has attracted investment from technology leaders and venture funds, and the company claims to have over $450 million in commercial contracts or commitments. There is also anticipation of expanded partnerships with telecom and enterprise providers, reflecting expectations of broader use in sectors where precise real-time location data delivers measurable benefit.

ZaiNar’s leadership emphasizes the practical effect of its technology.

“Physical AI needs a live, continuous feed of where everything is, and that dataset simply did not exist,”

said Daniel Jacker, co-founder and CEO, underlining the industry’s previous gap in this data.

“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,”

the company added, referencing concrete deployments in critical real-world settings.

The effort to transform passive connectivity into an active sensing layer has prompted more interest in protocol-agnostic solutions, especially as businesses seek to improve asset tracking, safety, and efficiency. ZaiNar’s approach stands out for using infrastructure already in place, sidestepping many challenges found with earlier beacon- or camera-dependent solutions. As device counts and AI-powered automation increase, the pressure is on for scalable, power-efficient, real-time positioning. Organizations interested in integrating such a platform will need to consider cybersecurity, privacy, and compatibility within their network environments, as these factors will greatly influence long-term adoption and ROI.

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Kaan Demirel
By Kaan Demirel
Kaan Demirel is a 28-year-old gaming enthusiast residing in Ankara. After graduating from the Statistics department of METU, he completed his master's degree in computer science. Kaan has a particular interest in strategy and simulation games and spends his free time playing competitive games and continuously learning new things about technology and game development. He is also interested in electric vehicles and cyber security. He works as a content editor at NewsLinker, where he leverages his passion for technology and gaming.
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