SciProton is not a generic text generator. It is a Retrieval Augmented Generation (RAG) engine built specifically for scientific taxonomy.
We don't just "read" text. We parse PDF layout to distinguish between methods, results, and discussion sections. Every sentence is converted into a 1,536-dimensional vector embedding, preserving its semantic meaning within the scientific context.
When you ask a question, we search across 200M+ vectors. Unlike keyword search, we find papers that match your intent.
Example: "How to fix..." matches with "Remediation strategies..."
Before the AI writes a single word, a separate model verifies the retrieved chunks. If the data isn't in the paper, SciProton is hard-coded to say "No evidence found" rather than hallucinating an answer.