Same engine. Same physics. Same mission brain.
Darkstar keeps simulation, operator training, mission execution, and replay inside one deterministic control system.
The same code that simulates the drone controls the drone.
Physics, terrain, adversary behavior, and human authorization are modeled before flight and preserved after flight.
Hive
Learns across missions. Trains the model. Deploys to the swarm.
Swarm
Coordinates in flight. No RF required.
Drone
Executes autonomous flight and human-in-the-loop engagement.
Simulation
Proves it works before it flies. GAIA terrain. Adaptive adversary.
No radio. No GPS.
No telemetry. No command link.
Drones coordinate through proprietary methods that leave zero RF footprint. Each drone knows what every other drone will do. Lost drones do not degrade the swarm.
RadioGPSTelemetryCommand linkRF signature
Type any city name and generate photorealistic 3D terrain.
Real buildings, roads, water, heights, and satellite imagery — the output feeds training, simulation, and mission rehearsal alike.
- Manual building classification
- Manual terrain measurement
- Hours of GIS stitching
- Dedicated GIS team, $200K+
- Automatic building classification
- Automatic from satellite data
- Automatic stitching
- Type a city name
Deterministic replay is a control surface.
Record, replay, branch, diff, and audit every decision. The point is not just training realism. The point is proving exactly why a mission behaved the way it behaved.
Same seed — identical result. Branch any tick. Diff any two runs. This is what DoD procurement requires, and what nobody else provides.