Process live video streams with state-of-the-art object detection, person tracking, and face recognition. Build intelligent camera systems with no-code tools.
Enterprise-grade computer vision features designed for real-world applications.
Detect and classify 80+ object types using state-of-the-art YOLO models. Process multiple streams simultaneously.
Track individuals across multiple cameras with advanced Re-ID models. Maintain identity across different angles and lighting.
Identify known individuals with high accuracy. Build searchable databases of faces for security and access control.
Define custom zones and trigger events when objects enter, exit, or dwell in areas. Perfect for retail and security.
Run inference locally on edge devices for low-latency processing. Support for NVIDIA GPUs and optimized models.
Visualize traffic patterns, occupancy trends, and detection events with real-time charts and historical analysis.
Connect any camera, configure your AI models, and start processing video in minutes. No machine learning expertise required.
From security to retail, computer vision transforms how businesses operate.
Smart Security builds intelligent surveillance that detects intrusions, recognizes authorized personnel, and alerts teams in real time, with face allowlist and blocklist plus automated event recording.
Retail Analytics reveals customer behavior through people counting, heat maps, dwell time, and queue management to optimize store layouts and conversion.
Workplace Safety monitors PPE compliance, flags restricted zone breaches, detects incidents, and generates compliance reports for industrial environments.
Traffic Management analyzes vehicle and pedestrian flow with vehicle counting, license plate recognition, and parking occupancy for smart city applications.
Use state-of-the-art models out of the box or bring your own custom-trained models. Deploy any ONNX or PyTorch model alongside the built-in library.
Support for all major camera types and video streaming protocols, so you can start processing footage from the hardware you already run.
Every stream flows through a four-stage pipeline: video input over RTSP or WebRTC, GPU-accelerated inference, object tracking with stable IDs, and event triggers. Detections fan out to workflows, alerts, storage, dashboards, the API, and webhooks.
It detects and classifies 80+ object types using state-of-the-art YOLOv8 and YOLOv10 models, tracks individuals across cameras with person re-identification, and recognizes known faces for security and access control.
RTSP cameras, IP cameras, USB webcams, video files, YouTube streams, and screen capture, plus WebRTC input. Connect the hardware you already run without changing it.
Yes. Alongside the built-in library (YOLOv8, YOLOv10, FastReID, InsightFace, and DeepSORT) you can deploy any custom-trained ONNX or PyTorch model.
No. You can run inference locally on edge devices for low-latency processing, with support for NVIDIA GPUs and optimized models, or process in the cloud.
Define custom zones and event triggers so detections fan out to automated workflows, alerts, storage, dashboards, the API, and webhooks.
Start processing video streams with AI in minutes. No ML expertise required.