ARIA - Biomedical Research Intelligence Assistant

ARIA — Autonomous Research Intelligence Agent — is a five-stage multi-agent system designed to eliminate the manual bottleneck in biomedical literature review. Researchers currently spend weeks identifying, screening, and synthesizing published evidence before any meaningful analysis can begin. ARIA compresses that entire workflow into under sixty seconds. Built on Llama 3.3 70B deployed on AMD MI300X hardware, the pipeline operates through five specialized agents: a Query Architect that generates optimized PubMed search strings from natural language input, a Literature Scout that fetches papers from PubMed and Europe PMC simultaneously, a PRISMA Filter that screens each paper against clinical relevance criteria, an Evidence Synthesizer that constructs a structured report with graded evidence levels and research gap analysis, and a Citation Builder that formats all references to standard. Beyond synthesis, ARIA offers a Predictive Model generating constructive and destructive research forecasts, a methodology comparison table, a follow-up question interface grounded exclusively in the retrieved dataset, and one-click PDF export of the complete review. The business case is direct: pharmaceutical teams, clinical trial designers, and academic institutions spend significant resources on systematic reviews that ARIA automates at scale. The system is hardware-optimized for AMD MI300X infrastructure, making it a viable enterprise deployment on existing clusters. ARIA does not summarize the internet — it synthesizes verified, source-linked, peer-reviewed evidence. That distinction is what makes it production-relevant for regulated research environments.