Satellite + Cameras ⢠Continuous Learning System
"Connect cameras. Learn patterns. Detect anomalies."
Quick Examples:
Each agent continuously learns from your camera feedsâbuilding Scene Memory, detecting anomalies, and improving predictions over time.
Traffic Cameras ⢠Route Intelligence
"Learns traffic patterns from camera networks. Predicts congestion."
Weather + Cameras ⢠Environmental Learning
"Learns environmental patterns. Correlates weather with observations."
City Cameras ⢠Urban Change Learning
"Learns urban development patterns. Detects construction and changes."
Global Cameras ⢠City Pattern Learning
"Learns city characteristics from worldwide camera networks."
Transit Cameras ⢠Transport Learning
"Learns public transit patterns. Predicts crowding and delays."
Street Cameras ⢠Activity Learning
"Learns local activity patterns. Knows busy hours and crowd levels."
All Sources ⢠Historical Memory
"Queries Evidence Memory across time. What happened, when, and why."
CCTV + Cameras ⢠Real-Time Learning
"Learns in real-time. SAM3 detection feeds continuous world model updates."
New multimodal agents coming soonâmore camera types, more learning, unified world model.
Coming soon: Drone feeds integrated into the self-learning world model.