Deepen Refinery Adds ROVR’s 90,000+ Hours of Multimodal Driving Data to Its Physical AI Data Marketplace

The addition expands Deepen Refinery’s growing catalog of real-world sensor data, supporting the development of autonomous vehicles, robotics and Physical AI.

SANTA CLARA, CA, UNITED STATES, October 5, 2026 /EINPresswire.com/ -- Deepen AI today announced that ROVR’s real-world multimodal driving data is now available through Deepen Refinery, Deepen’s neutral marketplace for verified data powering autonomous vehicles, robotics and other Physical AI applications.

Access to large volumes of sensor data is only one part of the Physical AI data challenge. AI teams also need to know what data they are getting, where it came from, whether it meets their requirements, and how quickly it can be incorporated into their development workflows. By combining ROVR’s large-scale real-world data collection capabilities with Deepen’s data infrastructure, developers gain access to sensor data through a workflow designed specifically for Physical AI development.

ROVR’s automotive dataset provides high-precision, forward-facing LiDAR and camera data, with each ROS2 bag containing LiDAR, imagery, IMU and GNSS data, including calibration parameters. The dataset spans driving environments across the Americas, Europe and Asia, with more than 90,000 hours of data available, while the underlying data pool is continuously refreshed as new data is collected.

Through Deepen Refinery, datasets can go beyond simply being listed in a marketplace. Deepen’s data infrastructure enables datasets to be catalogued, structured, enriched, validated and made easier to discover and evaluate, while maintaining information about data provenance and characteristics.
For developers, this means less time spent searching for, evaluating and preparing disparate datasets and more time focused on model development. For data contributors such as ROVR, Refinery provides a channel to make high-quality datasets discoverable to a broader ecosystem of AI developers and organizations.

“Physical AI teams don't just need more data, they need data they can understand, trust and actually use,” said Mohammad Musa, Co-Founder and CEO, Deepen AI. “ROVR brings significant scale and geographic diversity in real-world multimodal driving data. Deepen Refinery adds the infrastructure around that data, helping transform a valuable dataset into an accessible resource for teams building autonomous and intelligent systems.”

Deepen Refinery is built around the idea that the Physical AI ecosystem needs a more efficient connection between data generation and AI development.
The platform brings together data from specialized contributors and makes it easier for AI teams to identify datasets based on factors such as modality, geography, environment and application. Data can then be prepared and delivered in formats aligned with modern AI and robotics workflows, including ROS2, MCAP, HDF5, nuScenes and LeRobot.

Refinery also provides a foundation for data validation and quality assessment, helping teams understand the characteristics and suitability of datasets before incorporating them into their development pipelines.

This creates value on both sides of the marketplace:
- For data contributors: a way to monetize real-world data without having to build and operate their own distribution infrastructure.
- For AI developers: a centralized source for discovering and accessing data from multiple contributors, with greater visibility into provenance, characteristics and quality.
- For Physical AI development: a more efficient path from real-world data collection to model training, evaluation and deployment.

“ROVR has focused on building the infrastructure to capture high-quality representations of the physical world at scale,” said Gary Ling, Co-Founder, ROVR Network. “Deepen Refinery complements that work by providing the infrastructure to make this data accessible to the broader AI ecosystem. We are excited to make ROVR data available to teams building the next generation of autonomous vehicles, robotics and Physical AI.”

As autonomous vehicles, robots and other intelligent systems become increasingly capable, the demand for diverse and representative real-world data continues to grow. Yet the data ecosystem remains fragmented, with valuable datasets distributed across individual companies, research organizations and specialized data providers.

Deepen Refinery is designed to serve as a neutral data layer connecting these data sources with the organizations building Physical AI.

About Deepen AI

Deepen AI is building the verified data infrastructure for Physical AI. Its platform brings together data capture, calibration, curation, annotation and validation to help organizations develop safer and more reliable autonomous vehicles, robotics and other intelligent physical systems.
Deepen Refinery is Deepen AI’s neutral marketplace for Physical AI data, connecting data contributors with organizations building autonomous vehicles, robotics and other intelligent systems. Refinery enables teams to discover, evaluate, validate and access real-world datasets while maintaining visibility into data provenance and characteristics.
Learn more at www.deepen.ai/refinery

About ROVR Network

ROVR is building infrastructure for high-definition 3D data and Spatial AI. Its platform combines specialized data-collection hardware with a global network for capturing and processing real-world spatial data for applications including autonomous driving, robotics, mapping and AI.
ROVR’s LightCone platform integrates automotive-grade LiDAR, high-resolution cameras and high-precision positioning systems to capture detailed representations of the physical world.
Learn more at www.rovr.network.

Mohammad Musa
Deepen AI
+1 650-560-7130
info@deepen.ai
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