AI & Intelligent Solutions · Service 08 of 14

Computer Vision & Vision AI models that see what your team needs to know

O Clock Software, headquartered in Chennai, India, builds computer vision systems that inspect, detect, count, classify and read from images and video. We test on photos and footage from your real environment, with your lighting, angles and devices, and deploy to the cloud, mobile apps or edge devices.

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  • 2009Founded in Chennai
  • 1,000+Projects delivered
  • 12+Countries served
  • 100+Engineers in-house
  • 4.6★Google rating · 59 reviews

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What we build

Computer Vision & Vision AI: what we build

Image and video models for inspection, detection, counting and verification. Here are the six kinds of computer vision development work we are asked for most often.

Choosing the task

Which computer vision task fits your problem?

Naming the task correctly decides the data you need and the accuracy you can expect. This is how we frame it with clients before any labelling starts.

Task What it answers Example Data needed
Classification What is in this image? Damaged or not damaged Labelled images for each category
Object detection What is where, and how many? Counting vehicles in a car park Images with boxes drawn around objects
Segmentation Exactly which pixels? Measuring the area of a dent Images with outlined regions
OCR and text reading What does it say? Number plates and meter readings Sample images of the text
Anomaly detection Is anything unusual? Defects on a production line Mostly normal examples
Tracking and pose How is it moving? Queue length and safety zones Video with labelled movement

How we deliver

How we deliver Computer Vision & Vision AI

  1. 01

    Site and image review

    Cameras, lighting, angles and sample images from your environment.

  2. 02

    Labelling plan

    What to label, how, and how many examples are needed.

  3. 03

    Train and evaluate

    Models trained and measured on images they have never seen.

  4. 04

    Pilot on live capture

    Real cameras or phones, real conditions, measured results.

  5. 05

    Deploy and monitor

    Cloud, mobile or edge deployment with drift monitoring.

Technology

Technology for Computer Vision & Vision AI

Chosen per project for fit, maintainability and your team's skills.

Models

  • YOLO
  • Detectron2
  • Segment Anything (SAM)
  • Vision Transformers
  • Multimodal LLMs

Frameworks

  • PyTorch
  • OpenCV
  • TensorFlow Lite
  • ONNX

Labelling

  • CVAT
  • Label Studio
  • Roboflow

Deployment

  • NVIDIA Jetson
  • Core ML
  • TensorFlow Lite
  • Cloud GPUs

Straight answers

Is Computer Vision & Vision AI right for you?

We would rather recommend less than sell you more. Here is how we judge it.

A good fit when

  • The signal you need is visible in images or video
  • Capture conditions can be reasonably controlled
  • Examples exist or can be collected
  • Someone acts on the result

  • Capture conditions cannot be controlled at all

    Wildly varying lighting, angles or obstructions may limit accuracy; we test early before promising results.

  • A sensor would be simpler

    Weight, RFID or barcode may answer the question more reliably than a camera.

  • No examples exist and none can be collected

    Vision models need examples of what they should recognise.

Use cases by industry

Computer Vision & Vision AI by industry

The same capability, shaped by the data, rules and users of each sector.

Related work

Where we have shipped this

Platforms in production that use this capability. See all work

Related services

Often combined with Computer Vision & Vision AI

Solutions built on this service

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FAQ

Computer Vision & Vision AI FAQ

What can computer vision be used for in business?

Computer vision is used to inspect quality, assess damage, count items or people, read text such as number plates, verify identity documents and monitor safety. It is most useful where people currently look at images or footage to make a repeatable decision.

How many images do we need to train a model?

It depends on the task and the variety in your images. Simple classification can start with a few hundred labelled images per category, while detecting small or varied objects may need thousands; pre-trained models reduce the number needed, and a pilot shows whether more data helps.

Can computer vision run without an internet connection?

Yes. Models can run on edge devices such as NVIDIA Jetson units, smart cameras or phones, processing images on site and sending only results. This also keeps images local and gives faster responses.

Can you use our existing CCTV cameras?

Often, yes, if resolution, angle and lighting are good enough for the task. We review sample footage first and recommend camera changes only where the existing view cannot support the required accuracy.

How accurate is computer vision?

Accuracy depends on the task, image quality and training data. We agree target precision and recall for your use case, measure them on images the model has never seen, and pilot on live capture before full rollout.

How do you handle privacy with cameras?

We process only what the task needs, blur or discard faces where identity is not required, keep processing on site when possible, and follow the data protection rules of each market.

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MAIL US info@oclocksoftware.com
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