KORTHOS / ECOSYSTEM / PRODUCT

Mobileye REM

About

About Mobileye REM

REM collects compact road information from Mobileye-equipped production vehicles and combines it into high-definition Roadbook maps. The system records lane geometry, road boundaries, traffic signs, signals, driving paths and local behavioural context across the driven network.

Cloud processing aligns observations from many vehicles and updates the map as roads change. Mobileye systems use Roadbook data for positioning, foresight and driving-policy support within assisted and autonomous vehicles. The crowdsourced architecture expands coverage through vehicles already operating on public roads.

22 JAN 2026

Mobileye reports 2025 revenue of $1.89B and expanded Volkswagen robotaxi programme

07 JAN 2026

Mobileye agrees to acquire Mentee Robotics for $900 million

Timeline

  • Mobileye founder Amnon Shashua plans CEO transition

    2026-07-23 - Org Change - Mobileye said its board will run a comprehensive CEO search before the transition takes effect. Shashua has led Mobileye since its founding in 1999 and will remain on the board after stepping down as CEO. The transition comes as Mobileye expands beyond automotive autonomy into physical AI through Mentee Robotics.

    Source
  • Mobileye selected for future Stellantis ADAS programme

    2026-07-21 - Partnership - The programme covers selected future Stellantis vehicles rather than the full portfolio. Mobileye EyeQ6H compute is part of the announced system. Road Experience Management mapping will add cloud-enhanced road information.

    Source

Context

Market context

Mobileye REM is a crowdsourced mapping layer that builds and updates road intelligence from fleet vehicle data for autonomous driving systems.

  • Target environment: Urban roads, highways and autonomous vehicle operational domains.
  • Workflow context: Crowdsourced road mapping, HD map maintenance and road-intelligence updating using production vehicle fleet data.
  • Customer context: Autonomous vehicle developers and automotive OEMs using REM for mapping and localization.
  • Deployment model: Commercial software data product from a publicly traded company.
  • Commercial maturity: Mature mapping infrastructure with broad automotive industry adoption and real-world fleet data collection.
  • Adoption constraints: Requires compatible vehicle hardware and data pipeline integration.
  • Market position: Mobileye infrastructure layer for autonomy, turning production vehicle fleets into a map-update network.
  • Adjacent products: Autonomous driving maps, HD mapping platforms

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