A2 — AI Apps & Integration

Computer Vision & Image Recognition

Object detection, OCR and image classification for retail, security and healthcare, tested on real-world images.

Overview

Computer vision models often look great on clean sample images and then struggle with real-world lighting, angles, motion blur and poor cameras.

We define the accuracy you need, gather representative images, build or adapt models for detection, OCR or classification, and test them under the conditions they'll actually face.

What we do

01
Define what the system must recognise and how accurately
02
Collect and label representative images
03
Build or adapt detection, OCR or classification models
04
Test on real-world lighting, angles and image quality
05
Integrate results into your product or workflow

How we work

Step 1
Discover
We agree the use case, data sources and what a good answer looks like.
Step 2
Build
We integrate the model, your data and your product in short iterations.
Step 3
Evaluate
QA tests accuracy, safety and edge cases against an evaluation set before launch.
Step 4
Monitor
We track quality and cost in production and keep improving.

Who it's for

Retail and inventory teams reading products or labels
Security and monitoring use cases
Healthcare and document-heavy workflows

What you get

A requirements and accuracy target
A trained or adapted vision model
Real-world test results and known limitations
Integration into your product or workflow

Questions

Do we need thousands of labelled images?+

Not always. Modern pre-trained models can often be adapted with far fewer examples. We'll assess what your use case needs.

Can it run on a phone or device?+

Sometimes. It depends on speed and accuracy needs; we'll compare on-device and cloud options with you.

What does it cost?+

Hourly work starts from $25/hr. Fixed-price projects and dedicated teams are quoted after a free scoping call, based on scope, platforms and timeline.