Object detection & tracking
Finding, counting and following objects or people in images and live video.
AI & Machine Learning
Computer vision development
Turning images and video into decisions.
From tumour segmentation on MRI scans to reading walls and doors off architectural drawings, we train vision models that do in milliseconds what takes a specialist minutes.
Teach your software to see.
Computer vision lets software interpret images and video: find and count objects, outline regions, read text, spot defects, recognise products or flag anomalies in medical scans. Tasks that need a person to look at every image can be done in milliseconds, consistently, around the clock.
We have built vision systems for healthcare, where accuracy and explainability matter. We handle the full pipeline — collecting and labelling images, training and validating models, and deploying them where they need to run, whether that is a cloud API, a hospital server or a camera on the factory floor.
Computer Vision
What we offer
Image segmentation
Pixel-level outlines of regions — tumours, defects, rooms on a floor plan, crops in a field.
Medical image analysis
Models that assist with MRI, CT, X-ray and pathology images to help clinicians read scans faster.
Visual inspection
Automated quality control that catches defects on production lines more consistently than manual checks.
OCR & document vision
Reading text, tables and handwriting from scans, photos, drawings and forms.
Edge deployment
Optimised models that run on cameras, phones and on-premise devices without a cloud round trip.
When it’s the right fit
- People review images or video by eye, and it is slow or inconsistent
- You need to extract information from drawings, scans or photos at scale
- Quality control misses defects or cannot keep up with production
- You have imaging data and want to assist specialists, not replace them
How we deliver
- 01Image reviewWe study samples from your real conditions — lighting, angles, devices, awkward edge cases — before choosing an approach.
- 02LabellingA labelling guide and an annotated dataset, produced with your specialists wherever domain knowledge matters.
- 03Train & validateModels built on strong pre-trained backbones and tested on images they have never seen, with every error reviewed.
- 04Deploy where neededServed from the cloud, an on-premise server or directly on cameras and phones, depending on speed and privacy.
Technology
Tools we use for Computer Vision
- PyTorch
- OpenCV
- YOLO
- Segment Anything
- TensorFlow
- ONNX
- Python
- Label Studio
Frequently asked questions
How many images do we need to train a computer vision model?
Starting from pre-trained models, a few hundred to a few thousand labelled images per category is often enough for a first version. We assess your images early and can organise labelling if needed.
Can computer vision run without an internet connection?
Yes. We optimise models to run on edge devices, on-premise servers or phones, so images never have to leave your site.
Do you work with medical imaging data?
Yes — MedicMinder, our medical image analysis platform, works with MRI, CT and X-ray images. We handle medical data with strict access control and anonymisation.
Next step
Tell us what you want to build.
A free 30-minute consultation with an engineer — no obligation, reply within one business day.
Contact us