Label Insight aims to drive the food transparency revolution forward with cloud-based software

By Mary Ellen Shoup

- Last updated on GMT

Related tags Sugar Food

Food label transparency based on ingredients is becoming more important, Label Insight's VP of Data Dagan Xavier told DairyReporter, and he believes companies can capitalize by printing more claims and information on their labels. 

A recent study by Chicago-based software company Label Insight found that just 1% of chips and snacks are labeled dairy-free, however the company's ingredient analysis technology shows that 67% of chips and snacks are actually dairy-free based solely on ingredients.

"When a manufacturer is making a nutrient content claim such as 'Sugar Free' or "excellent source of protein", it is the manufacturer's responsibility to qualify and substantiate that claim,"​ Xavier said. Without proper substantiation a warning from the FDA can follow. 

"Label Insight can help this process as our processes are all automated. We can help manufacturers to determine whether or not a product qualifies for a nutrient content claim very easily, allowing them to be notified and take action."

Lack of dairy-free claim

The reason for the discrepancy is that, unlike most other allergens, the term "dairy-free" is not regulated by the FDA.

"Dairy-free is a term that's not regulated the same as gluten-free or any one of the other major allergens. So in that realm it's already a little bit behind. With dairy-free that term is not regulated, you're not seeing a lot of it on the labels,"​ Xavier said. 

As dairy-free becomes a more in-demand product claim, Xavier believes food products - and their labels - will become even more hyper-personalized in terms of allergens and ingredients.

The possibilities don't end with dairy, as gluten-free, or nut-free are claims that companies can make on their labels based on the ingredient list.

Company idea came from complicated diet

The idea for Label Insight began when Xavier's father became ill and he needed to restrict and add certain ingredients to his diet. Xavier, who was studying nutritional sciences at the time, decided to take his university knowledge and apply it towards helping his father decipher his new complicated diet. 

"I didn't really know there was no database to find out all of this stuff. So we started collecting all the data and that soon turned into this whole world of other people wanting to know why we're collecting this data and actually wanting access to that data,"​ Xavier said. 

Xavier and his team collected all the labels in Australia, which ended up being roughly 20,000 food products. However, at the time of this probe into food labels, there simply was not the revolution of food transparency there is now, Xavier explained. 

Adding context to data

Label Insight, which was still in its infancy, decided to switch focus to the US where there were many more datasets available. After developing a website to host all of its data, the company was contacted by an FDA scientist.

"Within hours we received an email from an FDA scientist who asked us whether we could actually show them all the food products in America that had zero grams of trans fat on the NFP, but still contained trans-fat ingredients,"​ Xavier said.

"And we could do that and we did do that in a couple of hours. That was the catalyst that got us into the FDA and really kept the lights on for our business. I think the value is that we were able to add context to the data," ​he added. 

'People want to know more'

Consumers are seeking more and more transparency in food ingredient labels, a call that manufacturers, retailers, and regulators have to answer, according to Xavier.

"With the rise of allergen-free consumer needs there is a high demand to have all the information on the label,"​ Xavier said. 

"People are looking to foods as a medicine and your retailers are almost educators in this industry.That's the revolution we're in right now. In order to achieve transparency, you require granular attribution."

Granular attribution is the process of deconstructing hundreds of basic attributes found on food packaging into hyper-granular data points, and then reconstructing and organizing the individual data points to apply context in the form of master attributes.

Label Insight's cloud-based data can include more than 15,000 consumer facing attributes from all sides of the packaging including data points derived from nutrients, ingredients, product description, marketing claims, and certifications, Xavier said.

For example, Label Insight can automatically analyze a product for the presence of artificial sweeteners, colors, flavors, or preservatives.

Related news

1 comment

consumers perception of environmental label on food

Posted by kadicha,

do you have any documentation report or studies regarding this topic please.
I want to make an investigation so I need some previous researches to compare my data
I want only EU data or UK because I live in the Uk

Report abuse