FMCG Data Labelling at Scale
A dedicated team of 20+ annotation experts delivering high-accuracy training data for retail shelf detection, SKU recognition, brand monitoring, and consumer behaviour models - trusted by FMCG leaders across the Middle East and North America.
Trusted by Leading FMCG Brands
From Saudi Arabia's largest dairy cooperative to North American packaged goods giants - our data fuels production-grade computer vision models.
500k+ shelf images annotated for SKU detection across 200+ dairy and juice SKUs
Cooking oil & sugar SKU recognition dataset for retail compliance monitoring
Beverage & water brand logo detection for GCC retail footprint analysis
Frozen & chilled FMCG planogram compliance dataset across KSA & UAE
Multi-class condiment & sauce SKU detection for North American retail CV models
Cereal & snack bar shelf-compliance segmentation dataset - 300k labelled frames
What We Label
Six core labelling disciplines - all battle-tested on real FMCG production datasets.
Product & SKU Detection
Precision bounding-box annotation across thousands of FMCG SKUs - dairy, beverages, snacks, frozen foods, and personal care. We deliver multi-class detection datasets with 99.2%+ annotation accuracy, enabling your models to recognise every product variant on a retail shelf.
Planogram & Shelf Compliance
Pixel-level segmentation of retail shelf images for planogram verification, out-of-stock detection, and share-of-shelf measurement across hypermarkets, supermarkets, and c-stores.
Packaging Text & OCR Extraction
Structured extraction of nutritional facts, ingredient lists, barcodes, QR codes, and expiry dates from product packaging images - supporting Arabic, English, and French text.
Brand & Logo Detection
End-to-end brand visibility annotation for in-store imagery and outdoor advertising. Our FMCG-trained team labels logos, display units, promotional materials, and in-aisle presence with brand-level precision.
Consumer Behaviour & Video Labelling
Frame-by-frame annotation of shopper journey videos - tracking dwell time, product pickup, shelf interaction, and path analysis to feed retail analytics and CV models.
Freshness & Quality Grading
Polygon-level segmentation and quality grading for fresh produce, dairy, and bakery lines - supporting automated freshness detection and waste reduction in retail and warehouse environments.
Our Labelling Process
Precision is built in from taxonomy design to final delivery - not bolted on as an afterthought.
Dataset Scoping & Taxonomy
We work with your ML team to define class taxonomies, annotation guidelines, edge cases, and quality thresholds before a single image is touched. Getting this right saves weeks of model-retraining.
Pilot Batch & Calibration
A calibration set of 500–2,000 images is labelled and reviewed with your team to align on ambiguous cases, label quality, and tooling configuration. Zero surprises at scale.
Production Labelling at Scale
Our 20+ annotator team runs parallel labelling pipelines across CVAT, Labelbox, or Scale AI. Daily throughput targets, automated consistency checks, and real-time dashboards keep velocity high.
Multi-Layer QA & Delivery
Every batch goes through senior-annotator review, automated shape validation, and a final QA audit. We deliver COCO JSON, Pascal VOC, YOLO, or custom formats - ready for training.
Tools & Platforms
We work natively in your toolchain or manage end-to-end in ours
Ready to build your FMCG training dataset?
Tell us your annotation type, volume, and timeline - we'll have a scoping proposal back within 24 hours.