AI Specialized for Food & Beverage Formulation
Matilde reduces physical testing and time-to-market without compromising quality, taste and food safety.
Discover the right solution for your R&D
Competitive advantages
Reducing Time to Market
Implementing AI systems accelerates the product development cycle, reducing time to market for new food products.
Matilde allows virtually thousands of combinations and scenarios to be simulated, eliminating unnecessary physical iterations and focusing resources on only the most promising prototypes. This approach enables informed decisions to be made faster, reducing the risk of costly delays. The result is a significant competitive advantage, with the ability to respond more quickly to market trends and consumer needs.
R&D cost reduction
MATILDE dramatically reduces product development costs:
- Minimization of physical prototypes: instead of producing samples to test different variants, AI simulation identifies the most promising formulations to be validated in the laboratory.
- Savings on expensive raw materials: used only for final prototypes, not for all exploratory testing.
- Optimization of staff time: formulators devote their skills to validation and fine-tuning, not repetitive testing of combinations.
Enhancement of know-how
AI processes laboratory data, formulation history, test results, and manufacturing feedback, creating an up-to-date and contextualized food R&D knowledge base. Consultation of formulations is immediate, greatly reducing the time it takes to search for technical information.
In companies, years of experimentation risk remaining in the memory of a few technicians. Matilde transforms this experience into a searchable digital asset: every tested formulation and every correlation between ingredients and final properties is archived and made available for the future. Know-how becomes a permanent asset, independent of people.
Case studies
Materials Informatics: The Emerging Field Combining AI and Materials Science
A Market in Definition In recent months, the landscape of materials research and development has begun to take shape more precisely around a key concept: Materials Informatics (MI). It is no longer an abstract term or a long-term vision but a well-recognized market area with dedicated reports, specialized companies, and international players already in the […]
Explainability and Innovation: How XAI Is Transforming New Product Development
XAI and Industrial Innovation: A Strategic Combination for Industry 4.0 In the landscape of industrial innovation, Explainable Artificial Intelligence (XAI) is revolutionising the process of new product development. Its ability to make algorithmic decisions transparent and understandable positions it as an enabling technology to improve operational efficiency, reduce time-to-market, and strengthen trust in artificial intelligence […]
AI to Accelerate Product Development – A Case Study in the Rubber Compound Sector
After exploring the applications in the cosmetics and food industries, today we share a concrete use case in the formulation of rubber compounds — a sector where the R&D department plays a key role in defining the optimal combination of ingredients and processes to achieve the desired performance. Every new formulation requires testing, experimentation, and […]
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GNN and Product Development: Intellico and the UniMI Department of Computer Science to the ECML PKDD 2024 Machine Learning Conference!
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Is AI a game changer for Cosmetics Companies?
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Revolutionizing food product development with AI – The success of Intellico at the Assolombarda Awards
In an industry where most new product launches require extensive development times and often fail to achieve the desired outcomes, Artificial Intelligence is emerging as a crucial game changer...
FAQ
1. How does AI facilitate the identification of alternative recipes?
Matilde accelerates the understanding and adoption of new solutions by analyzing unstructured knowledge from technical reports, external databases, technical reports, and internal documents, automatically extracting relevant information on ingredient properties and recipes and linking it to available experimental data.
2. How does AI work for food product development?
Food development AI analyzes historical recipe data (ingredients, percentages, physical properties) and predicts sensory characteristics of the final product (such as elasticity, pH, chewability, and taste) before laboratory testing.
3. Can Matilde replace ingredients while maintaining the same product properties?
Yes. Matilde simulates the impact of ingredient substitution on final product properties, showing if and how viscosity, stability, texture or sensory parameters change. Explainable AI indicates which alternative ingredients produce equivalent results, allowing reformulations for reasons of cost, availability, or regulatory compliance without compromising product characteristics.
4. Does Matilde integrate with existing laboratory systems (LIMS)?
Yes. Matilde natively integrates with leading LIMS such as Labware, Labvantage and Thermo Fisher Scientific, as well as PLM systems, MES, ERP and simple Excel/CSV files.
The integration allows historical formulations and test results to be imported automatically, without having to manually reload data or modify existing workflows.
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Intellico.ai is a provider of artificial intelligence-based software solutions with a presence in Italy and Europe.