BiomeStat, released by Medical Joyworks LLC on June 23, 2026, is an interactive AI bioinformatics agent designed to enable life science researchers to perform large-scale bioinformatics analyses interactively on mobile devices or web environments without coding. When a user inputs questions and datasets as if writing to an interactive AI, the system operates by dynamically compiling and executing validated R and Python bioinformatics libraries in a secure, isolated environment (Sandbox) in the backend, ensuring error-free operation. Just as a doctor diagnoses a patient based on complex medical knowledge, BiomeStat parses large volumes of raw sequencing data or analyzed data and provides researchers with intuitive and comprehensive analysis results in real-time. Traditional bioinformatics research has a high barrier to entry, requiring the separate establishment of high-performance computing servers and manual tuning of hyperparameters for unfamiliar and complex pipelines in a Linux command-line environment (CLI). BiomeStat virtualizes these cumbersome hardware provisioning and software installation processes through a cloud system, enabling even non-computer science researchers to perform professional analyses simply by interacting with the system on a mobile screen. This provides a similar innovation to the field of life science analysis as allowing a layperson with no web development knowledge to generate complex programs using natural language, guiding users to focus solely on the biological interpretation of the resulting data instead of spending unnecessary time on coding education. According to actual academic research validation cases, users can upload more than 1,000 genomic datasets and instruct the system to perform phylogenetic analysis and structural mapping completely autonomously. Internally, BiomeStat activates an organically structured agent workflow that includes phylogenetic reconstruction using IQ-TREE, molecular clock analysis using TreeTime, Bayesian phylodynamics estimation using BEAST2, and 3D molecular structure docking analysis using PyMOL. To prevent bottlenecks in this process, distributed computing nodes are dynamically generated and GPU infrastructure is expanded, allowing high-load computation processes that previously took several weeks to be completed safely and without errors within 24 hours.