An AI-powered Retrieval-Augmented Generation (RAG) tool for biomedical researchers.
General LLMs hallucinate badly when asked nuanced medical questions. MedDiscover solves this by strictly grounding answers in heavily-cited PubMed literature.
We use specialized, domain-trained encoders rather than generic OpenAI ADA models to vectorize text.
Fast retrieval of the top-k most relevant literature passages based on semantic cosine similarity.
The LLM synthesizes an answer referencing *only* the retrieved context, preventing hallucinated citations.