Computer Vision
Vision work succeeds or fails on data quality and edge cases. We start with your hardest examples, not your cleanest, and build pipelines that degrade predictably when conditions are poor.
What this includes
Document intelligence
Layout-aware extraction from scans, forms and invoices, including tables and handwriting.
Detection & classification
Object detection, defect spotting and quality inspection tuned to your tolerance for false positives.
Video understanding
Event detection and summarisation over live or archived streams.
OCR pipelines
Multi-engine OCR with confidence scoring and human review queues for low-confidence output.
Multimodal retrieval
Search across images and text in one index.
Edge deployment
Quantised models running on constrained on-site hardware.
What you end up with
- Manual data entry largely eliminated
- Confidence-scored output with review queues
- Predictable behaviour on poor-quality inputs
- Deployment on cloud or edge hardware
Tools we reach for
Frequently asked
How much labelled data do we need?
Often far less than expected. Pre-trained backbones plus a few hundred well-chosen examples beat thousands of careless ones.
Can it run without internet?
Yes. We deploy quantised models to on-site hardware where connectivity or data residency demands it.
Other work in this practice
RAG & Knowledge Systems
Turn scattered documents into a knowledge layer your AI can answer from — accurately, with sources.
Read moreAI Agents & Automation
Agents that use real tools, take real actions, and know their limits.
Read moreLLM Integration
Add language model capability to an existing product without destabilising it.
Read moreLet's talk about what you're building
Tell us the problem. We'll tell you honestly whether AI is the right tool, and what it would take.