Sparsh CCTV, Innoviz Technologies, and Cron AI Partner to Offer a Security and Intelligent Transport System (ITS) Solution Across India

Parties aim to deploy LiDAR-camera perception nodes for perimeter and area monitoring across India, unlocking real-time, edge-native intelligence for critical infrastructure

NEW DELHI and TEL AVIV, Israel, July 15, 2025 /PRNewswire/ -- Sparsh CCTV, one of India's leading manufacturers of smart cameras and integrated surveillance solutions with multiple government and enterprise clients in India, Innoviz Technologies Ltd. (NASDAQ: INVZ), a global automotive leader in LiDAR solutions, and Cron AI, a leading deep learning 3D perception provider, announced today they are collaborating to offer an integrated LiDAR-camera-vision perception platform, purpose-built for large-scale deployment across transport, perimeter security, railways, and critical infrastructure.

The announcement comes at a time when India's perimeter security sector is valued at USD 3.23 billion (2022) and projected to grow at a CAGR of 14% through 2030¹. The intelligent transport market, currently worth USD 1.44 billion (2024), is expected to more than double by 2033². Meanwhile, railway modernization and infrastructure investments exceed USD 1.3 billion³, driven by national programs like DFCCIL and Kavach. Together, these sectors represent over USD 1 billion⁴ in addressable opportunity for edge-native LiDAR-camera systems — with massive scaling potential through 2030.

With a footprint across 120+ cities, a network of 2,000+ partners, and an annual production capacity of 500,000+ security devices, Sparsh will lead go-to-market efforts, support integration, and explore local manufacturing for the unified sensing platform.

The edge-native perception nodes — combining high-performance LiDAR, deep-learning perception, and vision analytics — are expected to be part of a security infrastructure upgrade project which is planned to go live at critical infrastructure across India. These systems are intended to deliver real-time insights into vehicle movement, pedestrian safety, and perimeter activity — all processed on the edge, without reliance on cloud compute or high-power infrastructure.

"This partnership marks a major leap in how India can deploy high-performance, real-time sensing at scale," said Sanjeev Sehgal, Founder and MD of Sparsh. "By integrating global best-in-class LiDAR and 3D perception into our portfolio, we're equipping our customers — across cities, industries, and government — with intelligent systems that are built for Indian conditions and ready to scale."

Built for the Edge. Ready for India.

The integrated platform considers the complexities of Indian outdoor environments — heat, dust, glare, fog, and electrical instability — and delivers continuous, low-latency awareness at the edge.

• InnovizSMART LiDAR delivers long-range, high-resolution, uniform 3D coverage, built to perform in harsh weather and lighting conditions.
• Cron AI's senseEDGE processes every point in the LiDAR cloud using deep learning — not clustering — for greater accuracy, richer context, and consistent performance. It runs at just 8 watts, with no GPU or external infrastructure.
• Sparsh's vision systems contribute intelligent classification, layered redundancy, and real-time visual analytics — enhancing overall system reliability.

Together, they create a true sensor fusion platform, where 3D point cloud, video vision, and edge-native AI combine to deliver next-gen situational awareness — deployable in the near future.

"India's infrastructure needs intelligence that's fast, reliable, and frictionless," said Tushar Chhabra, Founder and CEO of Cron AI. "We built senseEDGE for exactly this kind of real-world complexity. With Sparsh and Innoviz, we're making 3D perception truly scalable across India's cities and critical infrastructure."

"Innoviz is proud to bring our rugged, automotive-grade LiDAR technology to one of the world's fastest growing infrastructure markets," said Omer Keilaf, CEO and Co-founder of Innoviz Technologies. "Paired with Cron AI's powerful edge-native perception and Sparsh's national reach, we are going to enable real-time intelligence for India's transport, security, and smart city initiatives."

From intersections, railways to critical infrastructure and perimeters, this is the future of sensing in India — real-time, intelligent, and built for deployment at scale.

About Sparsh CCTV

Sparsh is India's first STQC-certified CCTV camera brand and a leader in vision-based security. With operations in 120+ cities, exports to 10+ countries, and a partner network of 2,000+, Sparsh manufactures and deploys over half a million devices annually across sectors like law enforcement, transport, and critical infrastructure. www.sparshsecuritech.com

About Cron AI

Cron AI is a deep tech company transforming 3D perception for real-world infrastructure. Its platform, senseEDGE, uses deep learning to interpret every point in a LiDAR cloud — delivering accurate, robust insights on just 8 watts of edge compute. Offered via a Data-as-a-Service (DaaS) model, Cron AI makes real-time 3D intelligence easy to deploy and scale. https://cronai.ai/

About Innoviz Technologies

Innoviz is a global leader in LiDAR technology, serving top-tier automotive and industrial partners. Its solid-state LiDAR sensors and software meet the highest standards for safety, performance, and reliability — and are trusted worldwide across transport, defense, and autonomous systems. www.innoviz.tech

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Footnotes & Sources

¹ Grand View Research – India Perimeter Security Market Outlook

² Astute Analytica via GlobeNewswire – India ITS Market Forecast

³ See: Indian Railways CapEx Budget, DFCCIL Project, Kavach – PIB

⁴ Cron AI internal market sizing estimate based on infrastructure deployment potential and edge–native perception opportunity

Forward Looking Statements 

This announcement contains certain forward-looking statements within the meaning of the federal securities laws, including statements regarding the services offered by Innoviz, the anticipated technological capability of Innoviz's products, the markets in which Innoviz operates, Innoviz's projected future operational and financial results. These forward-looking statements generally are identified by the words "believe," "project," "expect," "anticipate," "estimate," "intend," "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, and in the case of our forward-looking revenues, actual orders or actual payments, 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 convert design wins into definitive orders and the magnitude of such orders, the ability to identify and realize additional opportunities, potential changes and developments in the highly competitive LiDAR technology and related industries, and our expectations regarding the impact of the evolving conflict in Israel to our ongoing operations. The foregoing list is not exhaustive. You should carefully consider such risk and the other risks and uncertainties described in Innoviz's annual report on Form 20-F for the year ended December 31, 2024, filed with the U.S. Securities and Exchange Commission ("SEC") on March 12, 2025 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. There can be no assurances that the Company will enter into definitive agreements, orders or receive payments with respect to the security infrastructure upgrade project referenced in this announcement, which is pending successful testing and demonstration. 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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SOURCE Innoviz Technologies