{"id":6844,"name":"Personalized Supplement Recommender","purpose":"A web application leveraging PubMed and potentially Qdrant for vector database storage, providing users with science-backed supplement recommendations based on their health goals and individual factors. Focus on transparency of the data.","profitable":1,"date_generated":"Monday February 2026 04:14","reference":"personalized-supplement-recommender","technology_advise":["Python","PostgreSQL","Medium"],"development_time_estimation_mvp_in_hours":220,"grade":8.0,"category":"healthcare","view_count":29,"similar_ideas":[{"id":6756,"name":"Personalized Supplement Recommendation Engine","grade":7.6,"category":"healthcare"},{"id":5331,"name":"Personalized Supplement Advisor","grade":7.2,"category":"healthcare"},{"id":8807,"name":"Personalized Meal Insights","grade":6.5,"category":"productivity"},{"id":6066,"name":"NutriTrack AI","grade":7.5,"category":"healthcare"},{"id":8815,"name":"Personalized Meal Recommendation API","grade":6.9,"category":"ecommerce"}],"source_headline":"Build supplement advisor using PubMed and Qdrant."}