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Accelerating Plant-Based Product

Faster, Smarter Innovation – Closing the Sensory Gap 

Customer Profile

A leading regional consumer packaged goods (CPG) company, operating as a division of a global food manufacturer.  The company focuses on developing innovative plant-based products for mainstream consumer markets. 

Challenge

For two years, the company’s R&D team had been working on a plant-based milk alternative  

but struggled to match the sensory profile of dairy milk. Key challenges included: 

• Prolonged iteration cycles due to reliance on external sensory panels. 

• Inefficient use of internal data and knowledge. 

• Difficulty integrating sensory feedback into formulation decisions in real time. 

AKA Solution

The company implemented an AI-assisted product development platform  

to centralize and accelerate the process. The platform integrated: 

• Sensory testing with a panel of 14 trained tasters. 

• Ingredient data, analytical measurements, and internal documentation. 

• Predictive AI insights, delivered in real-time, guiding formulation adjustments. 

• A custom AI model, trained on project-specific data and deployed on GCP, to analyze sensory results, predict  outcomes, and recommend improvements. 

Implementation Phases

1. Data Upload & AI Model Training – Consolidated ingredient, sensory, analytical, and documentation data into a  single platform; trained a custom AI model on client-specific data. 

2. Sensory Panel Integration – Embedded 14 trained tasters into the workflow for continuous feedback. 

3. Iteration with Real-Time AI Guidance – Leveraged AI insights during formulation to speed up decision-making  and close the sensory gap. 

KPIs 

• Reduced development cycle from seven to three iterations. 

• Completed final formulation in two months. 

• Consumer panel of 180 validated significantly improved taste and acceptance after AI-suggested flavorant  reduction. 

• Enhanced formulation accuracy and internal collaboration. 

Broader Impact On CPG Product Development

• Accelerated prototyping cycles. 

• Superior data curation and knowledge retention. 

• More impactful, insight-driven formulation decisions. 

• Stronger collaboration across distributed R&D teams.