Regulus Integrates Innoviz LiDARs to Improve Counter-UAS Performance in Complex Operational Environments
TEL AVIV, Israel, June 30, 2026 /PRNewswire/ -- Innoviz Technologies Ltd. (NASDAQ:INVZ) (the "Company" or "Innoviz"), a leading supplier of high-performance, automotive-grade LiDAR sensor platforms, today announced a collaboration with Regulus, focused on improving counter-UAS performance in complex operational environments, including defense solutions, homeland security, critical infrastructure and government facilities. By combining Regulus' expertise in counter-UAS with Innoviz's advanced LiDAR capabilities, the companies are addressing one of the industry's most difficult challenges: maintaining reliable situational awareness and precise tracking of low-altitude aerial threats at sub-kilometer ranges in urban and cluttered environments, including emerging fiber-optic controlled drones that are increasingly challenging conventional counter-UAS systems.
The collaboration is particularly focused on scenarios where conventional sensing technologies may face limitations, including operations in dense urban areas, around infrastructure, and in environments partially obscured by vegetation. By combining complementary sensing approaches, Regulus and Innoviz aim to deliver a more robust and reliable operational picture, enabling operators to maintain awareness of aerial threats even in conditions where traditional radar systems may struggle to provide sufficient accuracy or continuity.
"Innoviz is the eyes of the counter-UAS picture," said Omer Keilaf, Founder & CEO of Innoviz. "Our LiDAR delivers the precise object detection and high-accuracy 3D localization that give operators a clearer, faster read on low-altitude threats. Sensing and localization is where we focus, and where our technology adds the most value for the defense ecosystem."
About Innoviz
Innoviz is a leading provider of LiDAR technology, serving as a Tier 1 supplier to the world's leading automotive manufacturers and working towards a future with safe autonomous vehicles on the world's roads.
Innoviz's LiDAR and perception software "see" better than a human driver and reduce the possibility of error, meeting the automotive industry's strictest expectations for performance and safety. Innoviz's LiDAR sensors are designed to deliver exceptional range, resolution, and reliability, providing accurate 3D sensing in harsh weather conditions. Operating across the U.S., Europe, and Asia, Innoviz designs solutions for automotive OEMs, system integrators, municipalities, commercial enterprises, and other use cases worldwide. InnovizSMART is an off-the-shelf solution for security, defense and homeland security, intelligent traffic management, mobility, robotics, and aerial applications.
About Regulus
From combat-proven counter-UAS to fully autonomous System of Systems, Regulus is a global leader in autonomous point defense. Regulus integrates advanced, AI-driven C-UAS capabilities to provide automated defense against current and future aerial threats.
For more information about Innoviz, visit innoviz.tech.
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Forward Looking Statement
This announcement contains certain forward-looking statements within the meaning of the federal securities laws, including statements regarding the products and solutions offered by Innoviz, the anticipated technological capability of Innoviz's products, including performance under various environmental and operational conditions, the markets in which Innoviz operates, and Innoviz's projected future operational and financial results. These forward-looking statements generally are identified by the words "believe," "project," "expect," "anticipate," "estimate," "intend," "design(ed)," "strategy," "future," "opportunity," "plan," "may," "should," "will," "would," "will be," "will continue," "will likely result," and similar expressions.
Forward-looking statements are predictions, projections and other statements about future events that are based on current expectations and assumptions and, as a result, are subject to risks and uncertainties.
Many factors could cause actual future events to differ materially from the forward-looking statements in this announcement, including but not limited to, the ability to implement business plans, forecasts, and other expectations, the ability to achieve broader market adoption of Innoviz's products and solutions, the ability to identify and realize additional opportunities, potential changes and developments in the highly competitive LiDAR technology and related industries, the ability to maintain and scale initial deployments into long-term commercial relationships, the ability to advance collaborations into definitive development, integration, supply, or other commercial arrangements, the ability of Innoviz's products and integrations to meet applicable specifications and performance thresholds, the regulatory, licensing, and other requirements applicable to the defense and security markets and their potential impact on the timing and scope of Innoviz's activities in those markets, and Innoviz's expectations regarding the impact of geopolitical developments in the Middle East including the evolving conflict in Israel on its ongoing operations. The foregoing list is not exhaustive. You should carefully consider such risks and the other risks and uncertainties described in Innoviz's annual report on Form 20-F for the year ended December 31, 2025 filed with the U.S. Securities and Exchange Commission ("SEC") on March 4, 2026, and in other documents filed by Innoviz from time to time with the SEC. These filings identify and address other important risks and uncertainties that could cause actual events and results to differ materially from those contained in the forward-looking statements. Forward-looking statements speak only as of the date they are made. Readers are cautioned not to put undue reliance on forward-looking statements, and Innoviz assumes no obligation and does not intend to update or revise these forward-looking statements, whether as a result of new information, future events, or otherwise. Innoviz gives no assurance that it will achieve its expectations.
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