Ultralytics
Ultralytics, of Frederick, Maryland, develops the open-source YOLO family of computer-vision models, widely used for real-time object detection.
Founded in 2020 with 51 to 200 staff, it raised a 30 million US dollar Series A led by Elephant in 2025 and unveiled YOLO26 that September. It publishes guidance for airport uses such as ground operations, baggage and queue monitoring, and was joint winner of the Airports for Innovation AI challenge in May 2025. No airport or airline deployment is named.
No verified deployments yet
Ultralytics is profiled in the companies register, but no deployment has been verified against published evidence. Records are added as evidence is reviewed and graded.
Products & Solutions
2 productsUltralytics YOLO (YOLO11, YOLO26, YOLOv8 and prior versions)
Family of real-time object detection and computer vision models sold under commercial licenses for integration into third-party applications. Supports object detection, instance segmentation, object tracking, pose estimation, oriented bounding box detection, and classification.
Enables real-time visual monitoring and object detection in complex environments including airport tarmacs, terminals, and security areas without requiring purpose-built hardware beyond standard cameras.
- Real-time object detection at high speed
- Instance segmentation for precise object boundary detection
- Multi-object tracking across video frames
- Pose estimation for human body posture analysis
5 more features
- Oriented bounding box detection for directional object analysis
- Pre-trained on COCO and other large-scale datasets
- Fine-tuning capability for domain-specific applications
- Edge, cloud, mobile, and embedded device deployment
- 17+ export formats (ONNX, TensorRT, CoreML, TFLite, and more)
Technical specifications (4)
- Supports ONNX, TensorRT, CoreML, TFLite, and 14+ other export formats
- Python SDK and no-code interface via Ultralytics HUB
- Pre-trained on COCO dataset
- Compatible with edge devices and cloud APIs
Ultralytics HUB Platform
End-to-end cloud platform for training, annotating, and deploying YOLO computer vision models.
Provides a unified no-code and code-based environment for building, training, and deploying custom computer vision models without requiring deep ML infrastructure expertise.
- SAM-powered smart annotation for precise detection masks
- Supports 5 vision AI task types (detection, segmentation, classification, pose, oriented bounding box)
- 22 GPU configurations for cloud training (RTX 2000 Ada to NVIDIA B200)
- Live training metrics and experiment comparison
4 more features
- Deployment to 43 global regions with auto-scaling
- 17+ model export formats
- Real-time inference monitoring and performance analytics
- Scale-to-zero pricing (pay for active inference time only)
Technical specifications (4)
- 43 deployment regions globally
- Supports YOLO11, YOLO26, YOLOv8, YOLOv5 natively
- Universal dataset format support (YOLO, COCO, VOC, and more)
- Single-tenant dedicated endpoints available on Pro and Enterprise plans
Profile data from the Aerostack companies register; deployment records from the verified register. Evidence grades: T1 first-party confirmation, T2 credible reporting. See Our approach for how records are graded.