Artificial intelligence algorithms for nutritional assessment and recommendation

Problem addressed

The large volume of biological and behavioral data generated in precision nutrition is difficult to interpret without advanced tools. There is a need to translate these data into useful and safe recommendations for the end user.

What we do and how we do it

• We train AI models using data from clinical studies, metabolic profiles, and dietary habits.
• The algorithms generate personalized nutritional scores and recommendations tailored to individual goals (health, performance, well-being).
• We develop interactive dashboards for healthcare professionals and user-oriented applications for the general public.
• We ensure traceability and transparency in decision-making through explainable AI.

Key benefits

• Transformation of complex data into actionable nutritional decisions.
• Scientifically validated and personalized recommendations.
• Facilitates the integration of precision nutrition into clinical and sports practice.
• Continuous improvement through machine learning with new data.