Computer Vision Systems
Real-time video analysis, object detection, and AR pipelines.
We build vision systems that see what your cameras see — and act on it. From face clustering across thousands of photos to real-time production line defect detection, we handle the full pipeline: model training, inference optimisation, and integration into your existing hardware or software.
Who This Is For
You might need this if:
- ✅ You want to automate visual quality inspection on a production line
- ✅ You need face recognition or attendance tracking from CCTV
- ✅ You want to detect and track objects in real-time video
- ✅ You have a dataset of images and need to classify or cluster them
What we deliver:
- Trained CV model (YOLO, CNN, or custom architecture)
- Real-time inference pipeline for your camera or video stream
- Integration code for your existing system or hardware
- Performance benchmark (FPS, accuracy, latency)
- Full source code + model weights
- 30-day post-launch support
Vision Systems We've Built
Realtime AR Text Scanner
Augmented reality text detection and OCR pipeline using YOLO11 and EasyOCR. Real-time overlay with sub-100ms latency on standard hardware.
ClusterShot — Zero-Shot Face Clustering
Automated photo sorting by identity using InsightFace embeddings, DBSCAN clustering, and pgvector similarity search. Zero labelling required.
X-Pathology — Brain MRI Specialist
Temperature-calibrated EfficientNetB0 model for robust 4-class brain tumour classification from MRI scans. Production-grade with uncertainty estimation.
Frequently Asked Questions
Does the system need to run in real time?
It depends on your use case. Security monitoring and production line inspection typically need real-time inference (30+ FPS). Batch image classification can run offline. We'll design for your actual requirements.
Can I run this on my own hardware instead of the cloud?
Yes — this is actually one of our specialties. We can optimise models for edge devices (Raspberry Pi, Jetson Nano, industrial cameras) so everything runs locally with no cloud dependency.
What cameras or video sources do you work with?
Standard USB webcams, IP cameras (RTSP streams), phone cameras, industrial machine vision cameras, and pre-recorded video files. We've worked with most formats.
How accurate will the detection be?
That depends on your dataset size and image quality. We'll benchmark honestly before you commit. Our plant disease detector achieved 98.75% accuracy. Our cancer classifier hit 97.33%. Results depend heavily on data quality.
Ready to Deploy Vision AI?
Describe your camera setup and what you want to detect. We'll tell you what's feasible and how long it would take.
Book a Free Strategy Call