Uncover the Science
Behind SuppMatch
Explore the latest research and evidence-based findings that drive our personalized supplementation approach.
Data is extracted from a wide variety of external sources, including academic papers, official guidelines and reputable websites. Additionally, the expertise of Pharmacology Specialists, MD, PhD is leveraged to ensure the highest information quality.
Natural Language Processing techniques with utilization of Large Language Models and Vector Databases are used in data extraction.
Database
All collected data is organized in a proprietary format that facilitates efficient access by AI algorithms.
Important product data, such as ingredients, suggested dosage, flavour and other supplementary information, are gathered from the product description.
Natural Language Processing techniques with utilization of Large Language Models and Vector Databases are used in data extraction.
Database
All collected data is organized in a proprietary format that facilitates efficient access by AI algorithms.
In-depth physical questionnaire.
Database
Data from questionnaires is stored for use by AI algorithms and to monitor changes in user profiles over time
AI-Powered Precision
for Personalized Supplementation
.webp)
Your Feedback is Most Important to Us
Build SuppMatch with us, test the solution and share your opinion