Intelligence, surveillance & reconnaissance
Observe. Patrol. Detect. Report.
Tests, demonstrations and development records with clear source, scope and status.
Explore how AI GNC performs in demanding environments. Every test, demonstration and milestone is documented with real data, real terrain and real outcomes.

Real-world validation in challenging terrain.
We test in diverse environments — from rocky slopes to mud, snow and forest — to validate mobility, autonomy and system reliability.

See autonomy in action.
Live demonstrations showcase real operational use cases and system capabilities. They give a transparent view of behavior, integration and performance in realistic scenarios.

Raw tests. Real terrain. Unfiltered.
Access unedited video from field tests and demonstrations. See how the system performs in real environments, without staging or simulation.

See how it performs in real missions.
We test across reconnaissance, surveillance, payload transport and support missions. Each scenario validates adaptability and mission readiness.

Tests, partners and joint development.
We work with defense organizations, industry partners and research institutions to test, evaluate and co-develop new capabilities.

From test to deployment.
Track our progress from early prototypes to deployment-ready systems. Each milestone represents a step forward in autonomy, reliability and operational capability.
Concept visualizations of how AI GNC supports defense ground operations.
Observe. Patrol. Detect. Report.
Patrol. Monitor. Secure.
Follow. Alert. Assist. Protect.
Deploy. Extend reach. Aerial operations.
Our system is validated through both real-world testing and advanced simulation. Together, they provide a complete picture of performance, perception and autonomy.
Environment perception and navigation in real terrain.
Our onboard LiDAR provides high-resolution 3D mapping for autonomous navigation, obstacle avoidance and route planning. Real-world scans validate the system's ability to perceive complex terrain in dynamic conditions.
AI perception validated in virtual environments.
We use simulation to test and train perception models using instance segmentation and multi-object tracking. This ensures robust detection and classification of vehicles, personnel and objects before field deployment.
Explore the technology, market opportunity and evidence behind Tess Space. Cross-platform scaling will follow as each platform is validated.