PromptBio is a life science-specialized agentic AI platform established in 2023 in Pleasanton, California, USA, and fully relaunched in June 2026. Researchers can input scientific questions in natural language, and the platform automatically completes the entire process, from data exploration to pipeline execution, statistical analysis, visualization, and report generation, all within a single environment. Similar to how GPT understands and generates any text, PromptBio's core architecture, the Chief Scientific Orchestrator (CSO), automatically configures and executes appropriate analysis pipelines for any biological data, from bulk RNA-seq to single-cell RNA-seq and multi-omics integrated data. Under the CSO, three modules – PromptGenie (a human-in-the-loop multi-agent system), DiscoverFlow (an end-to-end automated workflow), and ToolsGenie (dynamic code generation for custom analysis) – collaborate organically, and a graph-based workflow engine manages data dependencies. Traditional bioinformatics analysis involves high technical barriers, such as R/Python scripting, command-line pipeline configuration, and cluster job management, which has hindered researchers' essential scientific thinking. In reality, even running DESeq2 can take half a day due to environment setup. PromptBio addresses this by simply asking, "What do you want to know?" in natural language, and the agent handles the rest of the technical processes. The division of labor within PromptGenie, where the DataAgent collects data from public databases, the OmicsAgent executes pre-validated pipelines, the AnalysisAgent performs statistical interpretation, and the QAgent handles interactive summarization and visualization, provides domain expertise fundamentally different from a single LLM chatbot. In addition, MLGenie automatically builds machine learning-based biomarker prediction models, and Omics Tools and Analysis Tools handle standardized omics pipelines and downstream statistical analysis, respectively, ensuring the depth of the analysis. Researchers at early adopter institutions such as UCSF, Northeastern University, and the South African CSIR have reported approximately a 30% reduction in analysis time compared to previous methods. For example, if a researcher requests, "Perform differential gene expression analysis followed by pathway enrichment analysis" on RNA-seq data from cancer patients, PromptGenie automatically generates and organizes a reproducible report, including DESeq2-based analysis, Gene Ontology/KEGG pathway enrichment, volcano plots, and heat map visualizations. Using DiscoverFlow, multi-omics workflows that integrate transcriptomics, proteomics, and metabolomics can be executed without code, and ToolsGenie dynamically generates executable Python/R code when custom analysis not included in standard pipelines is required. As a cloud-based SaaS, it is accessible on GCP, AWS, and Azure, and supports automatic scaling of GPU clusters to handle large datasets. It is also noteworthy that PromptBio has released its own benchmark (PromptBio-Bench), consisting of 244 expert-curated tasks, to provide a standard for evaluating the performance of LLM-based bioinformatics agents.