On-demand Multimodal Data Marketplace for Geospatial Intelligence.


The world's first hyperspectral point cloud dataset.

Large Coverage

Scalable data acquisition fleet, using TNC Vehicles & Customer Fleets

Frequent Updates

Weekly updates with fast turn around times.

Who We Serve

Vegetation Management

Each year, only 10% of utility poles are inspected causing gaps in disaster mitigation for fires and power outages. The lack of regular inspections contributes to these incidents. Hyperspec AI helps mitigate these fires by providing timely, actionable information for routine vegetation upkeep and maintenance.

Asset Management

Public works organizations transform their asset management with Hyperspec AI’s cutting-edge GIS integration, ensuring streamlined operations and proactive maintenance. Our advanced solutions provide real-time insights and predictive analytics, enhancing efficiency and decision-making while ensuring transparency for citizens.

Transportation & Mobility

Enterprise fleets thrive with Hyperspec AI's seamless GIS integration, transforming asset management into a streamlined, efficient process. Experience optimized routes, real-time monitoring, and unparalleled data accuracy, all driving superior transparency and operational excellence.

Our Technology

Hyperspectral Point Cloud

Hyperspectral point clouds integrate spatial (depth) information and spectral (reflectivity) data, providing a comprehensive dataset for geospatial analysis. This allows for precise mapping of terrain and infrastructure while identifying materials based on their unique spectral signatures. Such detailed information is invaluable in applications like environmental monitoring, urban planning, disaster management, and regulatory audits. By combining the physical layout with material properties, hyperspectral point clouds enhance the accuracy and efficiency of analyzing and managing natural and built environments.

Embodied AI

Multimodal data from vehicles, including visual, LiDAR, radar, and GPS information, enhances embodied AI robots' capabilities by providing a comprehensive understanding of their environment. Visual data aids in object recognition, while LiDAR and radar offer depth and motion information for navigation and obstacle avoidance. GPS data ensures precise localization, crucial for tasks requiring geospatial awareness. This combination creates robust situational awareness, enabling AI robots to operate more effectively and autonomously in dynamic settings.

Geospatial Intelligence

Advanced data integration offers significant value to society by improving environmental sustainability, enhancing urban infrastructure, and increasing disaster resilience. Detailed material monitoring supports better conservation and resource management, while comprehensive data integration enhances the accuracy of urban planning and infrastructure maintenance, leading to safer and more efficient cities. Autonomous robots can leverage this intelligence to perform critical tasks such as infrastructure inspection, agricultural management, and emergency response. This ultimately increases societal efficiency, safety, and resilience against various challenges.


Cybersecurity is paramount for protecting advanced data capabilities that are critical national security assets. The detailed environmental and urban data, combined with autonomous systems for monitoring, disaster response, and infrastructure management, must be secured from cyber threats to prevent breaches that could compromise national safety and vital operations. Securing this information from cyber threats is crucial to prevent breaches that could compromise national safety and vital operations. Robust cybersecurity measures are necessary to safeguard these strategic assets, ensuring that sensitive data remains protected from espionage and cyber-attacks, thereby fortifying national security and maintaining the integrity of critical functions.

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