AI service

ComputerVision.

Detection, recognition, OCR and visual inspection that turn images and video into structured data you can act on.

  • Object detection and recognition
  • OCR and document understanding
  • Automated visual inspection and quality control
  • On-device and edge deployment
Applied ML

01 / 05 · Your data

It starts from your data.

Records, images and history from your own systems. Most of the value is already sitting in a database.

A camera is only useful if software can understand what it sees. We build vision systems that turn pixels into decisions your business can act on.

Where it helps

Inspection and quality control. Spot defects, missing parts or wrong assemblies on a line, on every unit, without getting tired.

Documents and IDs. OCR and document understanding that read forms, invoices, IDs and handwriting into structured data your systems can use.

Counting and monitoring. People, vehicles, stock and safety compliance, turned from camera feeds into live numbers and alerts instead of footage nobody watches.

Recognition inside products. Features in your app that identify, classify or measure whatever the user points the camera at.

If someone on your team currently squints at images to make a call, there is usually a model that can help, and a quick way to find out.

How we keep it practical

Measure before building. We test what pre-trained models achieve on your images first. That number decides everything. Sometimes the problem is nearly solved already. Sometimes it shows that the camera setup, not the model, is the real project.

Small data, used well. Pre-trained backbones, careful augmentation and a small, well-chosen labelled set get most projects moving without an army of labellers. The system improves with use: every correction your team makes becomes training signal.

Deployed where it needs to run. Cloud for throughput, on-device or edge for latency and privacy. We optimise for the hardware you have. We have shipped enough mobile software to know what runs well on a phone.

Watched in production. Vision systems drift as lighting, products and camera angles change. Ours ship with the same evaluation and monitoring as our language-model work. Accuracy is tracked, not assumed.

The engagement shape

A short prototype on your real images, usually two to six weeks, establishes the accuracy you can expect. The production build then integrates the model into your line, product or workflow, with the retraining loop in place. Budgets follow the same logic as our cost guide. For business applications in more depth, read computer vision for business.

Have a vision problem? Send us a few sample images and we will tell you plainly whether it is feasible.

Questions we get asked

Before you ask.

Do you need a huge labelled dataset?

Not always. We can start with pre-trained models, careful augmentation and a small labelled set, then improve with your real data over time.

Can it run on-device or at the edge?

Yes. We optimise models to run on phones, cameras and edge hardware where latency or privacy matters.

What accuracy can we expect?

It depends on the task and the image quality, which is why every project starts by measuring a baseline on your real images. We tell you before the build whether the achievable accuracy clears your bar.

What does a computer vision system cost?

Focused systems usually run $40k to $150k or more, depending on data readiness, accuracy requirements and the deployment target. A short prototype first keeps the risk small.

Can vision models work with our existing cameras?

Usually, yes. We work with the hardware you have first, and only recommend new capture equipment when image quality blocks the accuracy target.

Get in touch

Tell us aboutthe work.

A workflow that takes too long, a model that keeps missing, a product that needs its next version. Write to us and we reply within a working day.

Discuss your use case hello@nftatoms.com