Services · Artificial intelligence · Computer vision development

Cameras and images that report what they see.

We provide computer vision development for detection, inspection, text reading, counting and video analytics. Models are trained on images from your own sites and run in the cloud or on devices next to the camera.
When cameras see people, privacy is designed in from the start: blurring, short retention and clear rules on who can view footage.
Get in touchAll AI services
Built for
Operations, quality and facilities managers in manufacturing, logistics, retail, property and transport.
Typical timeline
A pilot on one camera or one inspection point usually takes eight to twelve weeks, including image collection and labelling.
What you own
You own the trained models, labelled image sets, deployment code and any device configuration we create.
Rated
4.7 / 5 from 23 Google reviews

200+ companies across the US and the UAEFrom a first store to a listed developer

Modon
Majid Al Futtaim
HP
Belkin
Dulsco Group
OneClickDrive
Hanayen
HMS
Clocksprings
Ghezlan

What you get

What computer vision can do

Each use case starts with images from your environment, because lighting, angles and products vary from site to site.
Explain your project

  • Object detection

    Models find and label items in an image or video frame, such as vehicles, pallets, safety gear or products on a shelf. We train with YOLO and similar models on your images.

    Your team gets a live view of what is where without watching screens.

  • Visual inspection

    Cameras on a line or at a station flag scratches, missing parts, wrong labels or damaged packaging. Flagged items go to a person for the final call.

    Inspectors focus on the items most likely to have a fault.

  • OCR and document reading

    We read text from scans, photos, labels, meters and number plates using OCR models and OpenCV preprocessing. Low confidence reads are marked for review.

    Data printed on paper or objects ends up in your system without typing.

  • Counting

    Models count people, vehicles, items or animals passing a line or present in an area. Counts are stored over time for reporting.

    You get counts for planning without staff standing with a clicker.

  • Video analytics

    We analyse recorded or live video for events such as queues forming, zones entered or vehicles parked too long. Events are sent as alerts or written to a dashboard.

    Hours of footage become a short list of events worth looking at.

  • Edge deployment

    Models can run on small devices next to the camera, so video does not need to leave the site. Only results or short clips are sent to the cloud.

    Less bandwidth, faster alerts and less footage stored centrally.

  • Privacy by design

    When people appear in footage we blur faces where identity is not needed, keep retention short and restrict who can view raw video. The design follows GDPR and the data protection law in each market.

    You can use cameras for operations without creating a store of footage you do not need.

  • Labelling and retraining

    We set up a labelling workflow so your team can correct mistakes and add new examples. Models are retrained as products, layouts or lighting change.

    The model keeps up with changes at your site.

Who this is for

Where computer vision earns its keep

Vision works best where a person is looking at the same kind of thing many times a day.
01

Quality checks rely on tired eyes

Inspection cameras flag likely defects so inspectors check fewer items with more care.

A person makes the final decision.

02

You need counts or occupancy data

Counting at entrances, gates or shelves gives you reliable numbers for staffing and planning.

Faces can be blurred at the device.

03

Paper and labels still get typed in

OCR reads documents, labels and meters and posts the values to your system, with doubtful reads sent for review.

Works with photos taken on phones.

From camera to working model

  1. 01Site surveyWe review camera positions, lighting, network and what needs to be detected, and agree privacy rules.
  2. 02Collect and labelWe gather images from your site and label them with your team so the model learns what matters.
  3. 03Train and testWe train the model and test it on images it has not seen, including difficult cases such as glare and night.
  4. 04DeployWe install on devices or in the cloud, connect alerts and dashboards and monitor performance.

Technology

What we build this with.

Models are chosen per use case for quality, cost and where your data is allowed to go. The systems around them run on the stack below.

01Web

  • React
  • Next.js
  • TypeScript
  • Node.js
  • Laravel
  • WordPress

02Data and cloud

  • PostgreSQL
  • MySQL
  • MongoDB
  • AWS
  • Azure
  • Docker

Questions about computer vision

Often, yes.

Many IP cameras give a good enough picture. We check resolution, angle, lighting and frame rate during the site survey. Sometimes moving a camera or adding light makes more difference than a better model.

Services that usually go with this one.

Machine learning developmentPredictions from your own data, explained in plain terms.MLOps and AI platformsKeep your models working after launch day.AI automationAutomate the repetitive work, keep people on the judgement.

Tell us what the business needs. We will tell you what to build first.

Schedule a free consultation and get a written recommendation, with costs, before you commit to anything.

Get in touch

PROVEN RESULTS

4.7 / 5from 23 Google reviews