[News] Advanced Development Program Combining LiDAR and On-Sensor Perception Software for Future OEM Autonomous Vehicle Program

Innoviz Technologies Ltd., a leading supplier of high-performance, automotive-grade LiDAR sensor platforms, today announced a new software development agreement with a leading autonomous driving technology company. Under the agreement, the parties will evaluate on-sensor LiDAR perception capabilities for the InnovizTwo LiDAR platform and deliver a development plan. The collaboration extends Innoviz’s LiDAR embedded software to potentially deepen Innoviz’s role within the existing LiDAR supply relationship.

As autonomous vehicle programs advance toward series production, OEMs require that perception capabilities extend beyond the central compute stack and execute directly on the sensor itself. This on-sensor approach is designed to deliver standardized, safety-critical outputs that operate independently of the vehicle’s broader processing architecture, a design consideration for the most demanding autonomous applications. The agreement engages Innoviz to evaluate these capabilities natively within the LiDAR it provides, generating additional perception capabilities that may integrate directly into the partner’s autonomous vehicle architecture.

“Being selected to evaluate perception software on top of an existing LiDAR supply role is a strong signal that what we have built is being recognized across the full autonomy stack,” said Omer Keilaf, CEO and Founder of Innoviz Technologies. “This is Physical AI in practice, with intelligence that lives in the sensor itself, acting on the real world in real time. The fact that a leading autonomous driving program has chosen Innoviz for both the hardware and the evaluation for development of embedded perception reflects the confidence the industry is placing in our technology, and we are proud to be contributing to the future of autonomous vehicles at this level.”

TrendForce 2026 Infrared Sensing Application Market and Branding Strategies

Release: 01 January 2026

Format: PDF / EXCEL

Language: Traditional Chinese / English

Page: 168

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