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EXAMGURUXAI LABS

✦Service

Cameras that notice what matters.

We build computer vision systems that look at products, documents, shelves or sites and flag what needs attention — defects, missing items, safety issues or text to capture. Models are trained on your own images, tested against your quality standards and deployed where they are needed, from edge devices to the cloud.

Start a project How we build it

01What we build

What you get.

  1. 01

    Visual quality inspection

    Detection of scratches, cracks, misprints, missing parts or wrong labels on production lines.

  2. 02

    OCR on real-world scenes

    Reading number plates, meter values, labels, serial numbers and packaging text from camera images.

  3. 03

    Counting and tracking

    Counting items, vehicles or pallets and tracking movement through zones for operations reporting.

  4. 04

    Safety monitoring

    Alerts for missing protective equipment or entry into restricted areas, designed with privacy in mind.

  5. 05

    Edge deployment

    Models optimised to run on-site on devices such as NVIDIA Jetson or industrial PCs, with results sent to a dashboard.

02Use cases

Where it pays back.

  1. 01

    Manufacturing

    Inspect parts or packaging on the line and route rejects, with images saved for quality review.

  2. 02

    Retail

    Check shelf availability and planogram compliance from store photos.

  3. 03

    Agriculture

    Grade produce or detect crop issues from field and drone images.

  4. 04

    Logistics and warehousing

    Read labels, count packages and verify loading from dock cameras.

  5. 05

    Construction and facilities

    Monitor site safety and progress from fixed cameras, with alerts to supervisors.

03Process

How we build it.

  1. 1

    Define the defect or event

    We agree precisely what the system must detect and what accuracy is useful for your process.

  2. 2

    Collect and label images

    We capture and label a representative image set, including rare and borderline cases.

  3. 3

    Train and validate

    We train models and test them on held-out images and, ideally, a live trial on site.

  4. 4

    Deploy and monitor

    We deploy on edge or cloud, add dashboards and alerts, and retrain as conditions change.

Typical stack

  • YOLO
  • OpenCV
  • PyTorch
  • ONNX / TensorRT
  • NVIDIA Jetson
  • PaddleOCR
  • Label Studio
  • Python / FastAPI

04Where we work

Teams we work with.

05FAQ

Common questions.

ask us anything else →

01How many images do we need?

It depends on how varied your products and defects are. A focused inspection task can often start with a few hundred labelled images per class, then improve as more real examples are collected. We assess your data in the first phase and tell you honestly if more is needed.

02Can it run without an internet connection?

Yes. Models can be optimised to run on edge devices on site, so inspection keeps working even if the connection drops. Results and images can sync to a dashboard when the network is available.

03Do we need new cameras?

Not always. Existing CCTV or line cameras are sometimes enough; other tasks need better resolution, lighting or camera angles. We review your current setup and test sample footage before recommending any new hardware.

04How do you handle privacy for camera footage?

We process only what the task needs, can blur faces where people are not the subject, and keep footage for a limited period agreed with you. We design with local privacy rules in mind and involve your compliance team in the setup.

06More services

Other things we build.

Have a process worth automating?

Tell us about it — we'll reply with how computer vision could handle it, what data it needs and a rough plan. The first conversation is free.

Send a project brief examgurux@gmail.com