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Z3 detects body position and movement using ordinary WiFi signals—no cameras, no wearables, no privacy trade-offs.
Real-time spatial awareness with millisecond-level response. Everything stays local.
From hospitals to homes, organizations need to understand how people move through spaces—for safety, for wellness, for operational efficiency.
But every camera installed is a privacy liability. Every wearable is a compliance negotiation. Every cloud-connected sensor is a data breach waiting to happen.
The world needs spatial awareness without surveillance.
GDPR, CCPA, and emerging AI regulations are making camera-based monitoring increasingly difficult to deploy. Organizations need alternatives that respect privacy by default.
Every building already has WiFi infrastructure. Repurposing existing routers for spatial sensing eliminates hardware costs and deployment complexity.
Modern processors can run complex signal processing and neural networks locally. What required cloud servers three years ago now runs on a single gateway device.
The global elderly population is growing 3% annually. Falls are the leading cause of injury death in adults 65+. Passive monitoring that preserves dignity is urgently needed.
The gap isn't technology—it's architecture. Current systems force a choice between awareness and privacy.
Z3 eliminates that trade-off entirely.
Z3 analyzes the subtle distortions that human bodies create in WiFi signals. When you move through a room, your body reflects, absorbs, and diffracts radio waves in patterns unique to your posture and motion.
We decode these patterns into detailed body position maps—in real time—without ever capturing an image, a recording, or any personally identifiable information.
Uses standard WiFi routers and access points. No special hardware. No optical sensors. No visual data of any kind.
Millisecond-level latency at high frame rates. Fast enough for fall detection, activity tracking, and live occupancy monitoring.
Simultaneously track multiple individuals in a single space. Each person gets an independent full-body position map.
No images. No audio. No personally identifiable data. The system processes radio signal patterns—not people.
Fall detection, activity monitoring, and mobility tracking for eldercare and rehabilitation—without compromising patient dignity.
Detect survivors trapped in rubble through walls and debris. Vital signs monitoring including breathing rate detection at distance.
Z3 works by analyzing the fine-grained measurements of how WiFi signals travel between transmitter and receiver—data that standard routers already generate.
Human bodies distort these signals in predictable, measurable ways. Our proprietary engine decodes those distortions into precise body position data.
Standard WiFi routers continuously transmit signals. Z3 captures the signal propagation data—how radio waves interact with the environment and the people in it.
Our proprietary signal processing engine cleans the raw data—removing noise, correcting distortions, and extracting motion-relevant features in microseconds.
A deep learning model converts WiFi signal features into spatial body maps—bridging the gap between radio signals and human pose understanding.
The output is a full-body position map for each person detected—posture, movement, and location tracked continuously in real time.
Built with native low-level code for bare-metal performance.
Our proprietary engine processes WiFi signals orders of magnitude faster than general-purpose alternatives—enabling real-time tracking on low-cost hardware without cloud dependencies.
A 78-year-old resident in an assisted living facility gets up at 2 AM. No camera watches. No wearable buzzes. But Z3, running through the building's existing WiFi, detects the movement pattern.
When the body position data shows a sudden vertical-to-horizontal transition followed by no movement, the system triggers an alert within seconds.
Staff respond in under 3 minutes. The resident gets help without ever feeling watched. Their family gets peace of mind without surveillance footage.
"Monitoring that preserves dignity. That's what families actually want."
After a building collapse, first responders deploy portable WiFi transmitters around the debris field. Z3's disaster module begins scanning immediately.
WiFi signals penetrate through concrete and rebar where cameras and thermal imaging fail. The system detects subtle breathing patterns through layers of debris that block line-of-sight sensors entirely.
Survivors are located and prioritized automatically based on detected vital signs. Rescue teams focus extraction efforts where they matter most—guided by real-time data, not guesswork.
"WiFi signals go where cameras and dogs cannot—through walls, through debris, through darkness."
A corporate office wants to understand how meeting rooms are actually used—not just booked. Z3 provides real-time occupancy data through the existing WiFi network.
No badges to tap. No cameras to install. No privacy concerns to negotiate with the works council. Just accurate, anonymous people counts and movement patterns.
Facilities teams optimize HVAC and lighting based on actual occupancy. Space planners redesign layouts using real movement data. All without identifying a single person.
"We know how the space is used, not who uses it. That's the entire point."
High-performance native engine built and validated
Field validation with real-world environments
Production deployment and ecosystem
No cameras means no visual data. Period. There's nothing to leak, nothing to hack, nothing to subpoena.
Why it's defensible: Camera-based competitors cannot retrofit privacy. Their architecture requires visual data. Ours never touches it.
Every building already has WiFi. Z3 turns existing infrastructure into a sensing network—no new devices to buy, install, or maintain.
Why it's defensible: Competitors requiring dedicated sensors face per-room costs of $200-500. Our deployment cost approaches zero for WiFi-equipped buildings.
Our native signal processing engine delivers orders-of-magnitude speedup over conventional approaches. Lightweight enough to run on edge devices.
Why it's defensible: Years of proprietary optimization in signal processing and feature extraction. Deep systems engineering that is not easily replicated.
Healthcare, disaster response, smart buildings, security—same core engine, different application layers. Each new domain strengthens the platform.
Why it's defensible: Network effects across domains. Healthcare data improves motion models used by smart buildings. Disaster response validates extreme-condition performance.
Founder
20+ years building production software at enterprise scale. Principal Engineer leading backend technology for a ~$1.4B product. Played crucial technical roles in two successful acquisitions. Driving AI adoption initiatives with a focus on privacy-first, on-device systems.
"The question isn't whether we can sense people in spaces—it's whether we can do it without watching them. WiFi signals give us that answer."
— Ankur Sharma
High-performance engine built and validated
Proprietary algorithms with verified precision
API, real-time streaming, cloud deployment—production-ready
Architecture designed from day one to eliminate surveillance
See Z3 in action. Live demo of WiFi-based human sensing—how it works, what it detects, and where it's heading.