Vision Systems That See What Matters
We build production-grade computer vision systems — from real-time object detection to document OCR — trained on your data and deployed at the edge or in the cloud.
What We Build
Use Cases
Object Detection & Tracking
Real-time detection of people, vehicles, products, and defects in video streams.
Document OCR & Extraction
Extract structured data from invoices, IDs, forms, and handwritten documents.
Facial Recognition
Identity verification, attendance systems, and access control with liveness detection.
Quality Inspection
Automated defect detection on manufacturing lines with sub-millimetre precision.
Medical Imaging
Radiology assist tools, pathology slide analysis, and anomaly detection.
Retail Analytics
Shelf monitoring, customer flow analysis, and planogram compliance.
Tech Stack
What We Use & Why
PyTorch / TensorFlow
Deep learning frameworks for training custom vision models.
YOLOv8 / DETR
State-of-the-art object detection architectures for real-time inference.
OpenCV
Image preprocessing, augmentation, and classical computer vision pipelines.
ONNX Runtime
Cross-platform model deployment with hardware acceleration.
NVIDIA TensorRT
GPU-optimised inference for edge devices and data centres.
AWS Rekognition / GCP Vision
Managed vision APIs for rapid prototyping and hybrid deployments.
How We Work
Our Process
01 — Data Assessment
Evaluate your existing data, identify gaps, and design annotation strategy.
02 — Model Selection
Choose the right architecture based on accuracy, latency, and hardware constraints.
03 — Training & Validation
Train on your data with rigorous cross-validation and bias testing.
04 — Edge Deployment
Optimise and deploy to cameras, Raspberry Pi, Jetson, or cloud endpoints.
05 — Monitoring
Model drift detection, retraining pipelines, and performance dashboards.
Ready to get started?
Tell us what you need. We'll scope it out — free, no obligation.