Article
Product Development

AI at Work: Integrating clean label standards in product development

View our video clip to learn how product development teams can stay aligned with clean label standards and get to “right first time” results faster with AI-powered FoodChain ID Mentor™.

Meeting internal clean label standards can be one of the biggest challenges in product development. Frequent updates to internal policies can be hard to track, and when guidance isn’t easy to find or apply, teams risk using outdated information, leading to rework, delays and compliance issues. 

This video clip shows how FoodChain ID Mentor™, our AI-powered formulation guide, helps product development teams stay aligned with company standards and get to “right first time” results faster. 

The Challenge: Meeting internal clean label standards

Innovation teams must adhere to a variety of internal clean label standards while also juggling nutritional targets, regulatory thresholds and manufacturing constraints. 

Examples of clean label standards include:

  • Ingredient exclusion lists: Many companies maintain a list of ingredients that are not allowed in their products, even if they are legally permitted
  • Approved ingredient lists: Companies may curate positive lists of ingredients that are encouraged or approved for use
  • Processing and sourcing standards, such as sourcing non-GMO or organic ingredients 
  • Nutritional and formulation guidelines, such as sodium reduction targets or caps on added sugar per serving 
  • Transparency and labeling requirements to specify how products are marketed and labeled

These requirements are often housed in shared folders or PDFs, leading to version and accessibility issues. 

How can FoodChain ID Mentor help you meet company standards?

FoodChain ID Mentor reviews formulations in real time, delivering context-aware guidance across all critical aspects of product development, directly in our Recipes & Specifications and Formulation for PLM solutions. 

Instead of relying on manual checks late in the process, FoodChain ID Mentor proactively flags issues early and suggests alternatives, usage guidance and substitutions so that you can keep projects moving forward with confidence. 

FoodChain ID Mentor delivers AI-powered guidance across all critical aspects of formulation, including: 

  • R&D SOP Guidance  
    • R&D SOPs, guidelines and best practices 
    • Proprietary techniques and approaches 
  • Technical Feasibility/Manufacturability  
    • Ingredient/conditions that clog equipment 
    • Misused processing aids 
    • Process tolerance errors 
    • Poor ingredient sequencing leading to dispersion failures 
  • Quality and Food Safety    
    • Outdated shelf-life assumptions
    • Recurring stability issues previously documented 
    • Shelf-life ingredient conflicts 
  • Regulatory Compliance  
    • Exceeding additive thresholds  
    • Missed incorporated by reference 
    • Incorrect status assumptions (GRAS) 
    • Missed corporate mandates (like the clean label example in the video) 

FoodChain ID Mentor converts a company’s standard operating procedures (SOPs), best practices and regulatory rules—with FoodChain ID’s trusted global industry data—into embedded “skills” that provide guidance at every step of development. 

As policies change, business users can update skills instantly, without IT involvement, ensuring teams are always working with the most current requirements. 

By catching issues at the point of formulation, FoodChain ID Mentor helps: 

  • Keep development aligned with internal standards from the start
  • Reduce rework and last-minute disruptions that slow down launches
  • Accelerate time-to-market while maintaining compliance and consistency 

With FoodChain ID Mentor, teams can shift from reactive problem-solving to proactive, “right first time” outcomes. 

See FoodChain ID Mentor in action. Click here to learn more and book a meeting with our experts. 

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