The solution increased data extraction speed by 93%, reducing manual labor and processing thousands of images per minute.
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Client’s Challenge
Nielsen, a global leader in retail analytics, needed to streamline the process of extracting structured data from FMCG product images. With millions of images to process monthly, manual data entry was inefficient and error-prone. The task was further complicated by inconsistent ingredient labeling across languages and regions.
Our Solution
We developed a multi-stage AI pipeline combining image enhancement, region identification, deep learning models, and NLP for text correction. The system processes unedited product images, detects relevant text regions, extracts ingredient lists, and organizes them into a structured database. The solution is scalable, fully integrated with Nielsen’s systems, and handles diverse product lines, languages, and markets.
Client’s Benefits
The solution increased data extraction speed by 93%, reducing manual labor and processing thousands of images per minute. It achieved precision and recall rates of up to 95%.
