WORKFLOX Services

Teach Your Systems to See

Custom Computer Vision, Not Off-the-Shelf APIs

Generic vision APIs work for generic problems. When you need to detect a specific defect, read a specific document format, or track a specific object in your environment, you need a model trained on your data — not someone else's.

The Challenge

Where Off-the-Shelf Vision APIs Fall Short

  • Generic object detection doesn't recognize your specific products or defects
  • OCR tools fail on non-standard document layouts and Arabic script
  • No way to fine-tune accuracy for your exact operating conditions
  • Per-request API pricing becomes unsustainable at real volume
  • Data never leaves a third-party vendor's servers

Our Approach

What We Build

  • Custom-trained object detection models for your specific use case
  • Document OCR and data extraction, including Arabic and mixed-script documents
  • Real-time video analytics for monitoring, counting, and safety compliance
  • On-premise or self-hosted deployment for full data control
  • Model evaluation and retraining pipelines to maintain accuracy over time

Use Cases

What We Build For You

01

Automated Quality Inspection

Detect manufacturing defects, packaging errors, or product inconsistencies in real time using camera feeds on the production line.

02

Document OCR & Data Extraction

Extract structured data from invoices, ID documents, and forms — including Arabic and bilingual documents — straight into your database.

03

Retail & Inventory Vision

Shelf monitoring, stock counting, and planogram compliance using in-store or warehouse camera feeds.

04

Property & Construction Site Monitoring

Track construction progress, detect safety violations, and monitor site security using existing CCTV infrastructure.

05

Vehicle & License Plate Recognition

Automated access control, parking management, and logistics tracking using license plate and vehicle detection models.

06

Medical & Diagnostic Imaging Support

Assistive vision models for healthcare providers to flag anomalies in imaging data for human radiologist review — never a replacement for clinical judgment.

Our Process

Step-by-Step Development Process

01

Use Case Definition & Data Audit

We define the exact detection or extraction task and assess what training data already exists versus what needs to be collected.

02

Data Labeling & Preparation

We label and structure your training data, using existing labeled sets where possible to reduce cost and timeline.

03

Model Training & Evaluation

We train or fine-tune the model and evaluate it against real-world test data, not just the training set.

04

Integration & Deployment

We integrate the model into your existing camera feeds, document pipelines, or applications — on-premise or cloud as required.

05

Monitoring & Retraining

We set up accuracy monitoring and a retraining pipeline so the model stays accurate as conditions change.

Technology

Our Stack

We select the best tool for each job — not the most fashionable one. Every technology choice is justified by your performance, security, and maintainability requirements.

PyTorch
TensorFlow
YOLO
OpenCV
Google Cloud Vision
Tesseract / Custom OCR
ONNX Runtime
Python
FastAPI

FAQ

Frequently Asked Questions

How is custom computer vision different from using Google Vision or AWS Rekognition?

Off-the-shelf APIs are trained on general-purpose datasets and struggle with domain-specific tasks — a specific defect type, a proprietary document format, or objects unique to your industry. We train or fine-tune models on your own labeled data for meaningfully higher accuracy.

Can you build OCR for Arabic documents?

Yes. We build OCR pipelines that handle Arabic script, mixed Arabic-English documents, and non-standard layouts common in GCC business documents — government forms, invoices, and contracts.

Do you need a large dataset to train a custom vision model?

Not always. We use transfer learning on pre-trained models, which requires far less labeled data than training from scratch. For most business use cases, a few hundred to a few thousand labeled examples is enough to get production-grade accuracy.

Can computer vision models run on-premise for data privacy?

Yes. We deploy vision models on your own infrastructure or edge devices when data cannot leave your premises — common for healthcare, government, and security use cases.

How much does custom computer vision development cost?

A focused single-use-case model (e.g., defect detection or document OCR) typically costs $11,000–$27,000. Multi-camera, real-time video analytics systems range $27,000–$65,000 depending on scale.

Custom Computer Vision Development in USA, UAE & Saudi Arabia

WORKFLOX builds computer vision systems trained on your own data — not generic pre-trained APIs. From manufacturing quality inspection to Arabic document OCR, we engineer vision models that handle the specific conditions of your business, deployed on-premise or in the cloud depending on your data privacy requirements.

Arabic OCR & Document Intelligence for the GCC

Standard OCR tools consistently underperform on Arabic script and mixed-language business documents common across the GCC. We build custom OCR and document extraction pipelines specifically tuned for Arabic, bilingual, and non-standard document layouts.


Markets We Serve

Localized Expertise Across High-Value Regions

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