Innoviz

InnovizSMART Security System Deployed at Critical Infrastructure Sites in Israel

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Israeli LiDAR developer Innoviz announced today, for the first time, that its security solution InnovizSMART has been operationally deployed across several critical-infrastructure sites in Israel. The disclosure marks the product’s first confirmed real-world installations. The system is designed to protect sensitive facilities using 3D LiDAR sensing combined with AI-based analytics. The company recently also reported ramping up mass production of the new platform.

According to Innoviz, the installations were carried out over the past three months and the system is now used to detect, classify and track potential threats around secured facilities. For Innoviz — best known for automotive LiDAR sensors — the move represents a major milestone in entering a new market: infrastructure and security protection.

Alongside the deployment announcement, the company released detailed technical performance data for the first time. InnovizSMART can detect and classify objects at ranges exceeding 450 meters while scanning more than one million data points per second to generate an accurate 3D situational picture.

The system relies on a LiDAR sensor that creates a virtual perimeter fence around a protected site. When suspicious movement is detected within predefined zones, it can automatically activate surveillance cameras for visual verification and distinguish in real time between different target types — humans, vehicles or animals. The company highlights its ability to detect movement even behind physical obstacles such as trees and bushes, as well as operate in challenging weather conditions.

The platform integrates with existing enterprise security systems, including video-management and access-control platforms, and can track multiple targets simultaneously — a key requirement in complex security environments.

InnovizSMART originated as an adaptation of the company’s core automotive technology to the security sector. Over the past year Innoviz has actively promoted the product as part of a broader strategy to expand beyond the automotive market, which is characterized by long sales cycles and heavy dependence on major car manufacturers.

The company views InnovizSMART as a strategic growth engine with commercial potential across infrastructure protection, smart-city and intelligent-transportation markets. Unlike automotive deals, security projects typically move faster and generate revenue on shorter timelines.

As a result, the current operational deployment in Israel carries significance beyond the technological aspect: it serves as the product’s first commercial proof-point and signals a shift from announcements and pilot programs to real installations at paying customers.

The global infrastructure-security market is considered one of the faster-growing segments in the defense industry, with rising demand for advanced sensing capable of reliable detection in complex environments. Innoviz’s LiDAR technology competes with traditional solutions such as cameras and radar, offering higher accuracy and fewer false alerts.

Barak Light Guard security system unveiled

As part of its broader expansion into the defense and smart-perimeter-security markets, Innoviz also hosted an unveiling event this week at its headquarters for the Barak Light Guard system, developed jointly with Drive Group and Cogniteam. Senior representatives from the defense establishment and national infrastructure companies attended to evaluate the solution, which combines Innoviz LiDAR sensors with advanced AI algorithms.

Launched roughly six months ago, the system is designed to protect borders, communities and critical infrastructure, providing real-time alerts on intrusions and suspicious movement. It integrates Innoviz LiDAR with Cogniteam AI to identify and classify stationary and moving objects at distances of up to approximately 400 meters, even under poor visibility and harsh weather conditions.

NVIDIA’s Driving Model Poses a Challenge to Mobileye

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By Yohai Schweiger

While NVIDIA’s Rubin platform for next-generation AI infrastructure captured most of the attention at CES 2026 in Las Vegas last week, the company quietly unveiled another move with potentially far-reaching strategic implications for the automotive industry: the launch of Alpamayo, an open foundation model for autonomous driving designed to serve as the planning and decision-making layer in future driving systems.

The announcement is expected to influence not only how autonomous driving systems are developed, but also the balance of power among technology suppliers in the automotive value chain — with particular implications for Israeli auto-tech companies.

Most Israeli players, including sensor makers Innoviz and Arbe, as well as simulation and validation specialists Cognata and Foretellix, do not provide full vehicle systems but rather core components within the broader stack. For them, NVIDIA’s move could prove supportive. By contrast, the availability of an open and flexible planning model that allows automakers to assemble software-hardware stacks around a unified computing platform poses a strategic challenge to Mobileye, which has built its market position around a vertically integrated, end-to-end solution and full system responsibility.

NVIDIA DRIVE: An AI-First Ecosystem for Automotive

Alpamayo now joins the broader set of solutions NVIDIA groups under its NVIDIA DRIVE platform — a comprehensive ecosystem for developing intelligent vehicle systems. DRIVE includes dedicated automotive processors such as Orin and Thor, an automotive operating system, sensor data processing and fusion tools, simulation platforms based on Omniverse and DRIVE Sim, and cloud infrastructure for training and managing AI models. In other words, it is a full-stack platform designed to support automakers from development and validation through real-time deployment on the vehicle itself.

This aligns with NVIDIA’s broader push toward an AI-first vehicle stack — shifting away from systems built primarily around hand-crafted rules and task-specific algorithms toward architectures where large AI models become central components, even in layers traditionally handled by “classical” algorithms, such as decision-making.

In this context, Alpamayo plays a strategic role. For the first time, NVIDIA is offering its own foundation model for planning and decision-making, effectively re-centering the DRIVE platform around an end-to-end AI-driven architecture — from cloud training to execution on the in-vehicle computer.

The Vehicle’s Tactical Brain

Alpamayo is a large multimodal Vision-Language-Action (VLA) model that ingests data from multiple video cameras, LiDAR and radar sensors, as well as vehicle state information, and converts it into an internal representation that enables reasoning and action planning. Based on this, the model generates a future driving trajectory several seconds ahead. It does not directly control actuators such as steering or braking, but it determines the vehicle’s tactical behavior.

Unlike general-purpose language models, Alpamayo operates in a physical environment and combines perception with spatial and contextual reasoning. Its inputs include video sequences, motion data, and in some cases maps and navigation goals. The model performs scene understanding, risk assessment, and path planning as part of a single decision chain. Its primary output is a continuous trajectory passed to the vehicle’s classical control layer, which handles physical actuation and safety constraints.

Training such a model relies on a combination of real-world data and massive amounts of synthetic data generated using NVIDIA’s simulation platforms, Omniverse and DRIVE Sim.

The model is released as open source, including weights and training code, allowing automakers and Tier-1 suppliers to retrain it on their own data, adapt it to their system architectures, and integrate it into existing stacks — not as a closed product, but as a foundation for internal development. NVIDIA has also announced partnerships with industry players including Lucid Motors, Jaguar Land Rover (JLR), Uber, and research collaborations such as Berkeley DeepDrive to explore advanced autonomous driving technologies using Alpamayo.

Mobileye: A Challenge to the Full-Stack Model

An autonomous driving stack typically consists of several layers: sensors, perception, planning and decision-making, and control. Alpamayo sits squarely in the planning layer. It does not replace perception, nor does it replace safety-critical control systems — but it does replace, or at least challenge, the traditional algorithmic decision-making layer.

This enables a more modular system design: perception from one supplier, planning from NVIDIA’s model, and control from another Tier-1. This represents a conceptual shift away from closed, end-to-end “black box” solutions.

That is where the tension with Mobileye emerges. For years, Mobileye has offered a nearly complete stack — sensors, perception, mapping, planning, and proprietary EyeQ chips running the entire system with high energy efficiency. This model fits well with ADAS and L2+ systems, and even more advanced autonomous configurations.

However, foundation models for planning shift the balance. They require more flexible and powerful compute than dedicated ADAS chips typically provide, pushing architectures toward GPU-based computing.

While in some scenarios Mobileye perception components can be integrated into broader stacks, most of the company’s advanced autonomy solutions are offered as tightly integrated system units, which in practice limits the ability to swap out individual layers. Moreover, the very presence of an open planning model weakens the value proposition of proprietary planning software. Instead of developing or licensing dedicated planning algorithms, automakers can adapt an existing foundation model to their own data and operational requirements.

This is not an immediate threat to Mobileye’s core business, but over the longer term — as the market moves toward L3 and L4 autonomy and the decision layer becomes increasingly AI-driven — it represents a genuine strategic challenge to the closed, end-to-end model.

That said, Mobileye retains a significant structural advantage: it delivers a complete system and assumes full responsibility for safety and regulatory compliance. For many automakers, especially those without deep in-house AI and software capabilities, this is critical. They prefer a single supplier accountable for system performance rather than assembling and maintaining a complex “puzzle” of components from multiple vendors, with fragmented liability and higher regulatory risk.

Innoviz and Arbe: Sensors Gain Strategic Importance

For Israeli sensor suppliers such as Innoviz and Arbe, NVIDIA’s move could be distinctly positive. Advanced planning models benefit from rich, reliable, multi-sensor input. LiDAR provides precise three-dimensional geometry and depth, while advanced radar excels at detecting objects in poor lighting and adverse weather conditions.

This sensor data is essential for planning layers and decision-making models operating in dynamic physical environments. As a result, both companies are positioning themselves as part of NVIDIA’s ecosystem rather than alternatives to it. Both have demonstrated integration of their sensing and perception pipelines with NVIDIA’s DRIVE AGX Orin computing platform.

In a stack where decision-making becomes more computationally intensive and AI-driven, the value of high-quality sensing only increases. No matter how advanced the model, limited input inevitably leads to limited decisions.

Cognata and Foretellix: Who Verifies AI Safety?

Another layer gaining importance is simulation, verification and validation — where Israeli firms Cognata and Foretellix operate.

Cognata focuses on building synthetic worlds and complex driving scenarios for training and testing, while Foretellix provides verification and validation tools that measure scenario coverage, detect behavioral gaps, and generate quantitative safety metrics for regulators and safety engineers.

As AI models become central to driving stacks, the need for scenario-based safety validation grows, beyond simply accumulating road miles.

Both companies are aligned with NVIDIA’s simulation-centric development approach. Cognata integrates with DRIVE simulation and Hardware-in-the-Loop environments (where real vehicle hardware is connected to virtual scenarios) for large-scale testing, while Foretellix connects its validation tools to Omniverse and DRIVE to assess AI-based driving systems under diverse physical conditions.

Open Source, Semi-Closed Platform

Although Alpamayo is released as open source, it is deeply optimized for NVIDIA’s hardware platforms. Optimization for CUDA, TensorRT, and low-precision compute enables real-time execution on DRIVE computers, which are architecturally closer to GPUs than to traditional ADAS chips.

This fits into NVIDIA’s broader open-model strategy: the company releases open models for robotics, climate science, healthcare and automotive — but after deep optimization for its own computing platforms. The approach enables broad ecosystem adoption while preserving a performance advantage for those building on NVIDIA hardware.

In practice, this allows NVIDIA to expand AI into physical industries while shaping the computing infrastructure those industries will rely on.

A Threat to One Model, an Opportunity for Others

NVIDIA’s driving model does not herald an immediate transformation on public roads, but it does signal a deeper shift in how the automotive industry approaches autonomy: fewer hand-crafted rules, more general AI models, more in-vehicle compute, and heavier reliance on simulation and validation.

For much of the Israeli auto-tech sector — sensor providers, simulation vendors and validation specialists — this trajectory aligns well with existing products and strategies, and could accelerate adoption and partnerships within the DRIVE ecosystem. For Mobileye, by contrast, it signals the emergence of an alternative path to building the “driving brain” — one that does not necessarily rely on a closed, vertically integrated stack.

If autonomous driving once appeared destined to be dominated by a small number of players controlling entire systems, NVIDIA’s move points toward a more modular future — with different layers supplied by different vendors around a central AI platform. At least in the Israeli auto-tech landscape, many players appear well positioned for that scenario.

Innoviz Unveils InnovizThree, Expanding Its Vision Beyond Autonomous Vehicles

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Innoviz has officially unveiled InnovizThree, the next generation in its LiDAR sensor portfolio, marking a significant step forward both technologically and strategically. The new sensor, which will be demonstrated publicly for the first time at the upcoming CES exhibition, was designed from the ground up to be integrated inside the vehicle cabin, behind the windshield—a location long considered particularly challenging for LiDAR systems but increasingly favored by automakers.

InnovizThree is based on 905-nanometer Time of Flight technology and delivers a roughly 60% reduction in volume compared with its predecessor, alongside improved performance and lower power consumption. The sensor comes in an exceptionally compact form factor, measuring about 34 millimeters in height and weighing roughly 600 grams, enabling seamless behind-the-windshield integration. According to the company, it offers a detection range of up to 300 meters, high angular resolution of around 0.05 degrees, a wide horizontal field of view of up to 120 degrees, and a scanning rate of up to 10.6 million points per second. It supports operating modes of 10 or 20 frames per second and enables configurable regions of interest, allowing higher point density and resolution to be concentrated in critical areas of the field of view. The system is also designed to deliver a continuous point cloud without gaps within these regions and to detect multiple returns from a single laser pulse, improving performance in rain, fog, glass interference, and complex lighting conditions.

The emphasis on behind-the-windshield installation goes beyond aesthetics. In addition to improving vehicle design, internal placement protects the sensor from physical damage, dirt, and harsh weather, enables the use of existing heating and cleaning systems, and simplifies installation and maintenance. At the same time, it presents a significant optical challenge due to glass distortion and signal attenuation—challenges Innoviz says it has addressed through a combination of optical design, algorithms, and thermal management.

Alongside its core focus on autonomous driving, Innoviz is clearly signaling an expansion into new markets. InnovizThree is positioned as a general-purpose, high-precision 3D sensing platform suitable not only for vehicles but also for humanoid robots, drones, and physical AI systems—domains that demand compact, lightweight, low-power sensors with industrial-grade reliability.

Although this marks the product’s official launch, Innoviz CEO Omer Keilaf revealed InnovizThree several weeks ago during the company’s latest earnings call, as previously reported by TechTime. At the time, Keilaf emphasized that the product was born directly out of discussions with automakers, noting that placing LiDAR behind the windshield requires a smaller, more efficient sensor with sufficient performance headroom to compensate for optical signal degradation.

During the call, Keilaf also addressed competing sensing technologies such as FMCW and OPA, arguing that they are not yet mature enough for mass production. According to him, Innoviz’s choice of 905-nanometer Time of Flight enables the use of proven, widely available components, making the technology suitable for large-scale manufacturing and compliance with automotive standards.

The launch comes amid strong business momentum. Innoviz reported a 238% year-over-year increase in quarterly revenue to $15.3 million, a sharp rise in unit shipments, and continued progress in pilot programs and validation processes with major automakers for Level 3 and Level 4 systems, ahead of a planned start of serial production in 2027.

Innoviz Unveils InnovizThree LiDAR, Engineered for Behind-the-Windshield Automotive Integration

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[In the image above: the InnovizThree sensor (right) compared with the previous-generation InnovizTwo]

By Yohai Schwiger

Innoviz Technologies used its Q3 2025 earnings call on Wednesday to unveil the next generation in its LiDAR family, the InnovizThree sensor. CEO Omer Keilaf said the new model was engineered specifically to meet emerging requirements from the automotive industry. Based on 905nm Time-of-Flight, the device delivers improved performance, lower power consumption, and — most critically — a 60% reduction in volume, enabling installation in what he described as “the holy grail” location for automakers: behind the vehicle’s windshield, inside the cabin.

The sensor moves inside the vehicle

“This device was born out of conversations we’ve had with automakers,” Keilaf said on the call. “To place LiDAR behind the windshield you need a smaller, more power-efficient product with enough performance margin to absorb the optical loss going through the glass. InnovizThree was built exactly for this purpose, and can support urban Level 3 autonomy as well as seamless integration into the vehicle without roof- or grille-mounted protrusions.”

Automakers want LiDAR behind the windshield because it dramatically improves vehicle styling, protects the sensor from impacts, dirt and weather, leverages existing heating and cleaning systems, and simplifies installation and maintenance. Today, most LiDAR units in commercial and Level 3 vehicles sit on the front grille or fascia, while Level 4 autonomous vehicles typically mount LiDARs externally — on the roof or at the corners.

A technology ready for mass production

Integrating LiDAR behind the windshield is an engineering challenge due to optical distortion, thermal constraints and glass-induced signal attenuation. That requires smaller, more efficient and more robust sensors. InnovizThree builds on the architecture of the InnovizTwo — the platform that also underpins Innoviz Smart and the company’s short- and mid-range variants. The new model will debut publicly at CES 2026, and will serve as a central platform for derivative products for both automotive and industrial markets.

During the call, Keilaf addressed competing LiDAR approaches such as FMCW and OPA, arguing they are still far from production maturity. As he put it: “After many years of testing and experimenting, including OPA 1550 and FMCW LiDARs, it’s clear to us that 905 Time of Flight is the customer’s preferred solution. This industry can only scale on the solid ground of a proven mature technology.”

He emphasized that FMCW and OPA rely on materials and components that are not yet viable for automotive-scale production, whereas 905nm Time-of-Flight uses established, cost-effective, automotive-grade supply chains suitable for high-volume manufacturing.

Business momentum accelerates

Innoviz posted another record quarter: Q3 revenue jumped 238% year-over-year to $15.3 million. For the first nine months of 2025, revenue reached $42.4 million, up 2.3× from the same period in 2024. Gross margin was 15% for the quarter (26% year-to-date), while operating expenses fell 30% to $18.1 million, partly due to operational realignment and cost allocations associated with NRE payments. The company ended the quarter with $74.4 million in cash, no long-term debt, and reiterated that its ~$14M quarterly cash burn will continue to decline.

Innoviz reported a 10× increase in LiDAR shipments this quarter, supported by ramping production at Fabrinet. The company is progressing with Level 3 and Level 4 validation programs with top automakers, including another round of winter testing in northern Europe ahead of an expected 2027 SOP.

Level 4 autonomous trucks

A major development highlighted on the call was Innoviz’s progress with a global commercial truck manufacturer that selected the company as its LiDAR supplier for Level 4 Class 8 trucks, using multiple InnovizTwo units. Innoviz is already shipping sensors to the OEM’s data-collection fleet and is implementing software modifications.

“This is a significant milestone for us,” Keilaf said. “It demonstrates that our platform meets the stringent requirements of the heavy-duty trucking industry and positions us at the forefront of autonomous trucking.” The company expects to reveal the OEM’s identity in the coming weeks.

Volkswagen’s feedback

Keilaf also played excerpts from a conversation with Christian Senger, CEO of Volkswagen’s Autonomous Driving, Mobility & Transport Group (ADMT), responsible for the autonomous ID.Buzz program with MOIA and Mobileye.

Senger said: “Fully autonomous mobility becomes now really real… Our ID.Buzz has 27 sensors and nine LiDARs from Innoviz — three long-range and six short-range. The combination of all sensors and a strong compute platform gives the performance to understand the world.”

On LiDAR performance he added: “Our operational LiDAR with more than 350 meters of range gives us the distance we need for highway speed. There’s almost no difference between day and night. We have great results in rain and even foggy conditions. It helps the cameras understand the environment better.”

Senger praised the partnership: “We are creating together subsystems which have not been there ever… It is not only high-end performance, it is also industrial scale and fully automotive grade. I really love the openness and fast reaction from the Innoviz team.”

A market converging around Time of Flight

Keilaf noted that the automotive LiDAR market is consolidating rapidly. “The number of relevant automotive LiDAR players is declining… Some who had publicly committed to using FMCW are now expressing interest in transitioning to Time of Flight.”

After years of experimenting internally with both FMCW and OPA, Innoviz concluded that 905nm ToF is the only technology ready to scale in automotive volumes over the next several years.

Security applications: Innoviz Smart vs. cameras and radar

Beyond automotive, Innoviz reported growing traction in perimeter-security applications. The company completed its first installation of an Innoviz Smart–based fence-protection system and anticipates deploying dozens more by year’s end.

Keilaf described a comparative audit performed by a professional penetration-testing team: “Four out of ten times, the team avoided detection with the existing camera- and radar-based solution… Under the same conditions, they were not able to evade the Innoviz Smart solution at all.”

He added that the security sector remains “underserved,” both in sensing technology and in integration with VMS and command-and-control systems. Innoviz plans to offer software, analytics and 24/7 support alongside sensors — creating recurring-revenue opportunities.

Innoviz Secures New ISO Certification for In-House Testing Labs

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[Photo: Innoviz CEO Omer Keilaf. Credit: PR]

Israeli company Innoviz Technologies announced that its internal testing laboratories have received ISO/IEC 17025:2017 certification, one of the world’s most rigorous international accreditations for testing and calibration labs.

The recognition means Innoviz can now carry out the majority of critical tests for its LiDAR systems in-house, under a standard that guarantees accuracy, traceability, and technical reliability. For the company, this is a significant milestone in reinforcing its position as a Tier-1 supplier—a designation that allows it to sell directly to global automakers rather than only through system integrators.

In the automotive industry, standards are far from symbolic. Before any sensor is approved for mass-production vehicles, it must pass a long series of evaluations, from extreme performance testing to calibration and data-consistency checks. ISO/IEC 17025 certification addresses precisely this point: not the management or production processes, but the technical quality of the lab itself. The standard requires strict calibration procedures, meticulous documentation of every testing stage, rigorous equipment quality control, and proof that all results can be independently verified.

For automakers, the benefits are clear: shorter development cycles, higher reliability, and reduced reliance on third-party labs. In practical terms, car manufacturers can now rely on Innoviz not only as a technology provider but also as an accredited body that validates its own products to the industry’s highest benchmarks.

This marks a step up from the company’s previous certifications. Until now, Innoviz had already held IATF 16949:2016—the automotive industry’s core quality standard—alongside ISO 9001 for quality management, ISO 14001 for environmental management, and ISO 45001 for occupational health and safety. While those focus on organizational and management systems, the new certification zeroes in on testing accuracy and lab credibility.

The distinction carries strategic weight in the competitive LiDAR market, where suppliers are racing to secure spots on automakers’ sourcing lists. Achieving Tier-1 status demands not just advanced technology but also demonstrable compliance with stringent standards at every stage of validation. By obtaining ISO/IEC 17025, Innoviz is signaling that it doesn’t just build cutting-edge sensors—it also operates world-class testing facilities. That edge could prove decisive in winning future automotive contracts.

Innoviz Signs Major LiDAR Supply Deal with Global Truck OEM

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[Pictured above: Innoviz CEO]

Innoviz Technologies announced earlier this week that it has signed a significant contract with a global original equipment manufacturer (OEM) in the heavy-vehicle sector. Under the deal, Innoviz will supply its InnovizTwo LiDAR sensors for integration into Level 4 autonomous Class 8 trucks that will operate across North America.

While the company did not disclose financial details, it described the agreement as “major.” The initial phase will involve the delivery of early units to support data collection in pilot fleets, alongside the development of customized software to ensure seamless integration with the manufacturer’s operating systems.

“This win with a large and respected truck maker marks a milestone that reflects our ability to scale into new sectors,” said Omer Keilaf [pictured], CEO and co-founder of Innoviz. “These trucks require LiDAR sensors capable of withstanding extreme conditions while maintaining industry-leading performance. The InnovizTwo has proven itself with its high resolution, blockage resiliency, and the reliability needed to enable large-scale autonomy in heavy-duty vehicles.”

Barak 555 Launches Security System with Innoviz LiDAR and Cogniteam AI

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Barak 555, part of the Drive Group, announced yesterday (Tuesday) the launch of a new security solution, Barak Light Guard, developed in collaboration with two Israeli technology companies: Innoviz, a leading LiDAR sensor manufacturer best known for its work in autonomous vehicles, and Cogniteam, an AI company specializing in robotics. The system provides real-time alerts on suspicious activity and intrusions, with a detection range of roughly 400 meters and object classification capabilities enabled by the fusion of LiDAR and AI.

Cogniteam, founded in 2010, develops artificial intelligence and robotics solutions. Its Nimbus platform allows companies to build, manage, and update robotic software remotely via the cloud. Cogniteam works with defense, logistics, and agricultural robotics firms, providing them with tools to train AI models, deploy them across different platforms, and perform real-time software updates. For Barak 555’s system, Cogniteam supplied the AI analytics layer: its software processes data from LiDAR sensors and cameras, classifies objects, and significantly reduces false alarms—one of the biggest challenges in security control rooms.

LiDAR Moves Into Security

While widely used in autonomous driving and robotics, LiDAR is now gaining traction in security applications. Unlike cameras, which struggle in darkness, glare, fog, or heavy rain, LiDAR generates high-resolution 3D maps of the environment regardless of weather. These capabilities are crucial for systems monitoring open areas and complex terrains, where traditional surveillance tools often fall short.

The global security market is still in the early stages of adopting LiDAR. Pilot projects have explored its use for border protection, airport perimeters, and military or industrial sites. Companies such as Quanergy and Velodyne in the U.S. and Hesai in China are developing similar solutions, but the sector remains young and in search of mainstream adoption.

“Significant Advantage in Monitoring Open Areas”

Benny Lev, CEO of Barak 555, emphasized the breakthrough:
“For the first time, this LiDAR-based system enables long-range imaging and real-time detection of moving objects. It provides significant advantages for monitoring and securing open areas such as border zones, military sites, and critical infrastructure.”

The Drive Group operates several major Israeli infrastructure companies, including Highway 6 (Derech Eretz), Carmel Tunnels, Derech HaTzafon, Derech Btucha, and Barak 555. Barak 555 itself has been active for nearly 40 years, delivering large-scale projects in security, protection, and communications nationwide.

[Picture above: Cogniteam]