Open a world of applications with our AI-powered nutritional table data extraction

Product packaging contains a treasure trove of nutritional information – if only it could be easily utilised. Tables crammed with tiny text detail everything from calories and macronutrients to vitamins and minerals.

But this data remains trapped in analogue format, too laborious to extract insights at scale – until now.

Productify.ai’s cutting-edge artificial intelligence platform liberates nutritional information from packages, digitizing and structuring it for immediate use.

Our system goes far beyond basic data extraction. We normalise each data point into a universal nutrient ID code system for seamless integration through the use of GS1’s T4073 codes (https://gs1.se/en/guides/documentation/code-lists/t4073-nutrient-type-code).

For example, saturated fat becomes FASAT, total carbohydrates CHOAVL, sugars SUGAR, and so on. Vitamin C is matched to VITC, calcium to CA, and iron to FE. No matter the original format or layout, our AI structures nutrition facts into immediately actionable data.

Here is an example of a table from back of pack:

Productify.ai’s Extraction:

Another more complicated example:

The applications of standardised nutritional data are nearly endless:

  • Consumer goods manufacturers can track changes in nutritional profiles over time to spot unhealthy formula alterations.
  • Researchers can analyse nutrient amounts across product categories to inform public health initiatives and guidance.
  • Retailers can automatically flag products suited for specialized diets like gluten-free, keto, or vegan.
  • Personalised nutrition apps can harness the data to provide tailored diet insights.

Structured nutrition facts can also help shoppers better understand the foods they buy. Apps can compile and compare product information to highlight healthier choices within a category. Daily recommended values and percent daily values provide context for nutrients like fat, sodium, and fibre. Standardised data allows nutrition-focused search and discovery.

Saving time – a case study

Productify.ai’s extracted, standardised data has already enabled powerful real-world applications.

One major client is leveraging the structured information to automatically populate product catalogues. They map the nutrient ID codes to ingredient fields in their database. This instantly transfers details like calories, fat content, sodium levels, and more upon extraction.

Previously, these product details had to be manually entered line-by-line. But with Productify.ai’s AI-extracted nutrition facts, the client can fully automate the process. They can effortlessly build comprehensive catalogues while eliminating tedious manual data entry.

Unparalleled Accuracy with AI Extraction

Productify.ai utilises state-of-the-art artificial intelligence to extract and structure nutrition facts at unprecedented scale. Advanced OCR technology recognises text even when distorted, blurred, or in low resolution.

The AI accounts for challenging details to provide the nutritional data. The result is a bleeding-edge system capable of digesting nutrition facts tables with unparalleled accuracy.

Brands, researchers, retailers, and consumers can gain actionable intelligence from the nutritional data that Productify.ai can provide. Combining these datapoints creates a holistic product profile to inform everything from manufacturing to shopping.

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Andrew Trench

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