Storm is an automated research platform that coordinates multiple language model agents to conduct internet-based information gathering and generate structured, citation-backed articles. The system functions as a modular framework that grounds generated content in real-time web data, ensuring that all outputs are verifiable and evidence-based.
The platform distinguishes itself through a multi-agent discourse orchestrator that simulates expert dialogues to refine information discovery. By utilizing hierarchical concept mapping, the system organizes retrieved data into dynamic structures, allowing users to maintain research context and reduce cognitive load during complex synthesis tasks.
The architecture supports human-in-the-loop steering, enabling users to inject guidance and refine the research focus during active agent conversations. The pipeline is designed with a model-agnostic interface and modular components, allowing for the customization of knowledge curation, outline generation, and article writing workflows to meet specific project requirements.
