ORIGIN AI®
We build production-grade computer vision systems — from real-time object detection to medical image analysis — powered by the latest YOLO architectures, transformers, and custom deep learning pipelines.
Each capability is delivered end-to-end — from data collection and annotation to model training, optimization, and production deployment.
View ProjectsReal-time localisation and classification of multiple objects in images and video streams. Deployed using YOLOv8, YOLOv11, YOLOv12 and custom-trained models for domain-specific use cases including agriculture, healthcare, retail, and security surveillance.
Pixel-perfect masks for every detected object — enabling precise area measurements, disease boundary detection, and surgical planning. Used extensively in plant pathology, medical imaging, and industrial quality control.
Single or multi-label classification with state-of-the-art accuracy using EfficientNet, ViT, and fine-tuned foundation models. Applied to plant disease grading, medical scan diagnosis, defect detection, and satellite imagery analysis.
Precise landmark detection for humans, animals, plants, and industrial objects. Powers pose estimation for physiotherapy apps, crop growth stage monitoring, sports biomechanics analysis, and gesture-based interfaces.
Every project is built for real deployment — optimised for edge devices, cloud APIs, or embedded systems depending on your latency and accuracy requirements.
Agriculture
Deployed YOLO-based detection model that identifies 38 disease classes across 14 crop species in real-time. Farmers use the mobile app to photograph leaves — the system instantly detects, segments, and grades disease severity, recommending treatment within 2 seconds.
Healthcare
Automated segmentation of retinal layers and classification of AMD, DME, and CNV conditions from OCT scans with ophthalmologist-level accuracy.
Security
Real-time person detection and tracking across 16 simultaneous camera feeds. Alerts generated within 300ms of intrusion event with zero false positives during trials.
Healthcare / Sports
17-point body landmark detection for real-time posture scoring and exercise rep counting. Deployed on mobile — no specialised hardware required.
Document AI
End-to-end document processing pipeline extracting structured data from invoices, receipts, and forms with layout-aware transformer models.
Remote Sensing
Multi-spectral satellite imagery segmentation to assess crop health, estimate yield, and detect irrigation anomalies across large farmlands.
RF-DETR (Real-time Detection Transformer) is a state-of-the-art object detection architecture developed by Roboflow. It combines the accuracy of transformer-based attention mechanisms with inference speeds competitive with YOLO — delivering the best of both worlds for production CV systems.
Unlike traditional anchor-based detectors, RF-DETR uses a DINOv2-pretrained encoder with a real-time decoder head — achieving 60+ FPS on a single GPU while outperforming YOLOv11 on COCO benchmarks at equivalent model scales.
Tell us about your dataset, domain, and accuracy requirements. We'll design a solution that fits.