Designed for the field
Local sensing, processing and storage allow missions to continue when connectivity is unavailable.
AUTONOMOUS FIELD INTELLIGENCE
AI that can move, observe and understand the physical world.
SpatialXplor combines autonomous robotics, sensing, edge AI and spatial intelligence to help experts inspect, understand and act on real-world environments.
Autonomous survey mission · No manual control · Field-to-cloud intelligence
01
02
03
Physical world → spatial intelligence
Observe · locate · interpret · review
THE PLATFORM
A common intelligence layer for different field environments.
SpatialXplor is not tied to one industry, robot or sensor. The platform connects autonomous machines with the sensing and AI required by each domain problem.
01MobilityNavigate the environment
→
02SensingObserve physical conditions
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03Edge AIInterpret locally
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04Spatial contextKnow where it happened
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05Expert reviewTurn evidence into decisions
Robot and sensor extensible
The current prototype uses a quadruped robot, LiDAR and five-band multispectral imaging, but the architecture is not tied to that hardware.
Secure field-to-cloud architecture
SpatialXplor builds on secure multi-tenant cloud technology that has previously undergone independent penetration testing as part of an earlier commercial deployment.
Expert in the loop
The objective is to extend specialist observational reach, not replace expert judgement.
APPLICATIONS
One architecture. Three very different environments.
The common problem is physical observation at scale. The sensing, AI and operating model change according to what the domain expert needs to know.
01 / RESOURCES
Mineral exploration
Autonomous close-range geological observation and spatially referenced evidence for geologist review.
- Multispectral and geological sensing
- AI-assisted material screening
- GPS-denied spatial context
02 / INFRASTRUCTURE
Infrastructure inspection
Repeatable autonomous inspection of plant rooms, service corridors and industrial environments.
- RGB and thermal observations
- Change and anomaly detection
- Repeatable inspection routes
03 / AGRICULTURE
Agriculture & environment
Persistent close-range observation of pasture, crops, vegetation, soil and environmental conditions.
- Multispectral vegetation sensing
- Condition and change monitoring
- Ground-level spatial evidence
WORKING PROTOTYPE
From autonomous mission to expert review.
The current system integrates autonomous movement, LiDAR/SLAM, multispectral imaging, AI analysis, spatial mapping and secure field-to-cloud evidence.
01
ROBOT MISSION
Autonomous field operation
Autonomous survey mission — no manual control.
02
FOXGLOVE
Real-time field intelligence
LiDAR, live video, multispectral observation and AI analysis.
03
SPATIALXPLOR CLOUD
Mapped evidence and AI reports
Survey events, imagery, mapped observations and reports.
EXECUTION CAPABILITY
Built by people experienced in turning complex technology into production systems.
Technology leadership. The team brings more than two decades of experience across enterprise software, AI, cybersecurity, cloud infrastructure and production systems.
AI research. The AI capability includes researchers experienced in deep learning, multimodal learning, transformers and complex scientific datasets.
Production engineering. The broader engineering capability has delivered secure commercial platforms across healthcare, media and advertising.
PARTNERSHIPS & PILOTS
Where could autonomous field intelligence create measurable value?
SpatialXplor is seeking domain partners and field-validation opportunities across resources, infrastructure, agriculture and environmental monitoring.
Discuss a Field Validation Pilotcontact@spatialxplor.com