DIFARYX

DIFARYX is an AI-powered scientific workflow intelligence platform designed to help researchers move from raw experimental data to defensible scientific decisions. Modern R&D teams generate large amounts of characterization and experimental data, but interpreting evidence, identifying uncertainties, and deciding what to do next remains a manual and time-consuming process. DIFARYX addresses this challenge by providing an evidence-centered reasoning workflow that connects experimental observations, scientific interpretation, validation gaps, and recommended next actions. The platform guides researchers through a structured workflow: Research Objective → Experimental Context → Evidence Workspace → Agent Reasoning → Validation Gap Analysis → Next Experiment Recommendation → Notebook & Report Generation DIFARYX supports scientific data interpretation across multiple characterization techniques, including XRD, XPS, FTIR, and Raman spectroscopy. Instead of producing unsupported conclusions, the system applies scientific guardrails that distinguish evidence from claims, explicitly communicate uncertainty, and highlight missing validation requirements. Using AI reasoning agents, DIFARYX evaluates experimental evidence, generates traceable reasoning paths, identifies limitations in available data, and proposes the most relevant follow-up experiments. The platform then converts the complete reasoning process into reproducible notebook records and structured scientific reports. For this hackathon, DIFARYX demonstrates how AI can transform disconnected experimental results into transparent, evidence-based scientific workflows. By combining scientific reasoning, validation-aware decision support, and automated documentation, DIFARYX helps researchers accelerate discovery while maintaining scientific rigor and reproducibility.