Unified and Scalable
All-Scenario Smart Driving Solutions

OpenExplorer™ is a toolchain independently developed by Horizon Robotics, designed specifically to address the challenges of embedded development - long development cycles, high investment, and steep barriers to entry. Based on the Journey™ series solutions, it incorporates three core capabilities: post-quantization of models, quantization training, and compilation optimization. This toolchain provides comprehensive, end-to-end support for developers, including model quantization, optimization, compilation, simulation, deployment, and debugging. With more than 200 ecosystem partners empowered, Horizon's toolchain, refined through large-scale production experience, ensures reliable lifecycle support for the development and mass production of upper-layer software and hardware systems.

To address the challenges of domain controller integration complexity and software adaptation, Horizon Robotics has introduced the Horizon Matrix™ standard reference design, based on the Journey™ series solutions.
As a standardized computing platform, Matrix meets the differentiated validation, testing, and development needs of partners, covering the full development process—from desktop development and on-vehicle data acquisition to production reference workflows.
By opening this reference design, Matrix significantly reduces the costs associated with development, adaptation, and deployment for OEMs and ecosystem partners. This accelerates the development of more competitive advanced smart driving products and expedites mass-production deployment. Matrix also seamlessly integrates with Horizon Robotics' system software and algorithm solutions, further lowering the development barrier and enhancing production R&D efficiency.
Horizon Robotics collaborates with Matrix-authorized hardware IDH partners to provide customized services and professional technical support for OEMs and Tier 1 suppliers with differentiated design needs, accelerating the mass-production progress of customers' smart driving solutions.

Horizon Qoho™ is dedicated to collaborating with partners across the supply chain, offering sensor solutions that balance performance, cost, and reliability for mass production of smart vehicles. This includes sensor selection, testing and validation, as well as cost and quality control, providing standardized sensor solutions for the smart automotive industry.

Horizon continues to drive the standardization of vehicle-mounted camera solutions and interfaces. By quantifying calibration and acceptance standards for vehicle-mounted cameras' internal parameters, we aim to build a comprehensive image testing and evaluation system, covering both objective and subjective assessments. Through open interface definitions, testing specifications, and quality standards, we aim to help customers and partners quickly adapt solutions and reduce adaptation costs.

Horizon AIDI™ is a cloud infrastructure built for software development and iteration in smart vehicles. It helps OEMs and ecosystem partners establish a closed loop spanning data mining, labeling, training, optimization, deployment, evaluation, management, and performance analysis.

With flexible value-added services such as 4D labeling and an algorithm repository, AIDI boosts development efficiency and significantly reduces mass-production delivery costs.

Introduction: TogetheROS™·Auto addresses pain points such as high integration complexity for advanced smart driving systems, poor multi-source software compatibility, and low iteration efficiency. Built on the TogetheROS in-vehicle OS, it provides a production-oriented smart driving application development kit for professional developers and ecosystem co-creation, offering an open, flexible, right-sized ecosystem solution for OEM and Tier 1 integration.

Through open source and openness, TROS.A collaborates with ecosystem partners to continuously enrich ecosystem building blocks, significantly lowering development barriers, enabling faster production iterations, and accelerating the adoption of high-level smart driving.