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Data for computer vision
Images, OCR, object detection, retail data, documents, and local environments — collected in the actual visual contexts your model will operate in.
Vision models trained on generic or Western-sourced imagery underperform on Arabic signage, regional packaging and storefronts, and document layouts that don't match a Latin-script assumption. We collect and annotate visual data in-region, in context.
What this covers
- Object detection and classification in retail, street, and document contexts
- Arabic OCR — printed and handwritten, including mixed-script documents
- Document AI — invoices, forms, ID documents (with appropriate consent and handling)
- Mapping and geospatial imagery annotation
Worked example. A retail-AI buyer needed 50,000 grocery-shelf images across Riyadh stores, annotated for product recognition — see the full image data page for how that project was scoped and reviewed.