Deepen AI Autonomous Vehicle Platform Debuts at CES 2026

On January 5, Deepen AI announced that it will unveil its Deepen AI Autonomous Vehicle Platform at CES 2026, introducing new capabilities aimed at strengthening sensor fusion accuracy, cutting calibration complexity, and enabling autonomous vehicle and robotics teams to scale deployments with higher confidence in safety-critical operating environments.
The latest release of the Deepen AI Autonomous Vehicle Platform is designed to address one of the biggest bottlenecks in autonomy programs: ensuring that multiple sensors such as cameras, lidar, and radar work together as a single, reliable perception system while remaining easy to calibrate and validate during development and deployment.
Deepen AI Autonomous Vehicle Platform enables live multi-sensor calibration
At the CES 2026 demonstration area, visitors will be able to physically reposition sensors mounted on a vehicle or robotic setup and immediately observe how the Deepen AI Autonomous Vehicle Platform performs automatic calibration across multiple sensor types. This hands-on experience highlights how teams can remove manual alignment steps and significantly improve repeatability.
Key benefits demonstrated at the booth include:

• Real-time calibration between different sensor modalities

• Reduced dependency on manual tuning and physical measurement

• Faster setup cycles for complex autonomous systems

By automating these steps, development teams can shorten validation timelines while maintaining high levels of precision required for safety-critical autonomy.
Deepen AI Autonomous Vehicle Platform introduces the VLA framework
Deepen AI will also preview its upcoming VLA framework as part of the Deepen AI Autonomous Vehicle Platform, which is designed to connect raw multi-sensor inputs with higher-level perception, reasoning, and action planning. This framework enables autonomous systems to move beyond data collection toward more context-aware decision making.
The VLA framework focuses on:

• Linking sensor fusion outputs to semantic understanding

• Enabling more reliable autonomous behavior planning

• Supporting robotics and vehicle platforms with scalable intelligence

This approach allows developers to build systems that better understand their surroundings and respond more predictably in real-world conditions.
Deepen AI Autonomous Vehicle Platform expands scenario-based testing
Alongside platform and framework updates, Deepen AI will showcase a growing scenario library within the Deepen AI Autonomous Vehicle Platform. This library is designed to support simulation, testing, and safety validation by providing a wide range of driving and robotic operation scenarios.
The scenario library helps teams:

• Validate perception and planning algorithms across diverse environments

• Strengthen safety assurance workflows

• Standardize testing across different autonomous programs

By integrating these scenarios directly into the platform, Deepen AI aims to make safety-focused testing more consistent and scalable for global development teams.
With its new calibration tools, VLA framework preview, and expanding scenario library, the Deepen AI Autonomous Vehicle Platform at CES 2026 highlights how the company is enabling autonomous vehicle and robotics developers to move faster while maintaining the reliability and safety demanded by next-generation mobility systems.