AI food label extraction

Food Label Data Extraction and Validation

Food Label Data Extraction and Validation

By using the MaxinaAI solution, the customer was able to automate the extraction of food label data and confirm its compliance with country-specific regulations.



Seeing various foreign products on the shelves of local stores may seem like a normal thing, but there is a complicated process behind it all. Before these products can be sold, their labels must meet specific requirements set by the destination country.

Since each country has different standards when it comes to food and food-related products, it is vitally important that food exporting companies comply with country-specific regulations. 

Most of the time this process requires an incredible amount of human resources and is usually very time-consuming. The traditional process is often very complex, labor-intensive, and error-prone. It includes dedicated staff who manually extracts data from product labels and manually verifies compliance with country regulations.

Our Swiss client, C-Labs SA, develops solutions to transform food regulatory compliance and was aware of the industry challenges mentioned above. To fight the complexity and time-consuming nature of this process, a customer decided to automate it with the help of the MaxinaAI team.

That is why they approached us and asked for a solution that would simplify obtaining information on food ingredients and their verification with the specific regulations of the country.


At the core of our solution was computer vision, a technology that helps computers gain high-level understanding from digital images or videos, label images, and automate tasks that the human visual system can perform.

Let´s take a look at how we incorporated computer vision in our solution. For the start, we created a model that classified all nutritional labels from uploaded pictures and performed text extraction on them which was done directly from the food products’ nutritional label and the information on the ingredients was later compared with the desired country regulation. 

To identify the text on the product package, Optical Character Recognition (OCR) was used. OCR is a technology that helps the user transform desired documents (images from paper documents, scanned images, etc.) into searchable and editable data. 

This technology makes difficult data extraction possible. Some products (such as potato chip bags) have a softcover, which causes the text written on them to bend or, due to the light, the text does not show well, making it difficult to extract the text. However, OCR technology makes it possible and feasible.

Another benefit of OCR is accelerated information search and extraction. So for example, if a colleague sends you a photo of a document taken by the camera, it will be difficult for you to quickly search for the information or even more so, edit it. With the help of Optical Character Recognition, you can digitize the text contained in the document making searching and editing information easy and convenient.

The same benefit was acquired for our client. They did not have to manually extract all the information from the food package, as with our solution it was possible to extract the product information automatically from the user-uploaded image, including nutritional information, weight, and manufacturer name.

Before MaxinAI solution:

Before MaxinAI solution

After MaxinAI solution:

After MaxinAI solution

A dedicated team has trained custom machine learning models using open-source dataset and product images from Amazon. In combination with several cloud OCR services, we managed to provide a high-quality API service. The multi-step pipeline was created to process large amounts of data in a scalable way.

To make this process easier, we also created a system with a user interface where the information was displayed in a structured and visual way that helped and simplified the work process for the end-user.


  • Customized YOLO implementation on PyTorch
  • spaCy + scikit-learn for NLP adjustment
  • Dockers and Google Cloud for continuous delivery 
  • Google OCR and AWS Textract
  • Scrapy to collect data from different sources

Skip the boring manual work

The old-school data entry process includes manual labor done by people that has proven not only time-consuming but prone to inaccuracy and human error from time to time. With the MaxinAI solution, you can automate this process saving yourself time and trouble.

Today, no one should be burdened with mundane and repetitive tasks. With intelligent automation, you and your staff can take on more important tasks that have a greater impact on business performance.

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© 2021 - MaxinAI | All Rights Reserved
© 2021 - MaxinAI | All Rights Reserved