Stanford STORM
Autonomous deep research system synthesizing multi-perspective, citation-backed Wikipedia-style reports
About Stanford STORM
Stanford STORM (Synthesis of Topic Outlines through Retrieval and Multi-perspective Question Asking) is an open-source AI research system developed by Stanford University. It autonomously conducts deep web investigations, generates diverse stakeholder interview perspectives, and synthesizes exhaustive, citation-backed long-form reports. Unlike standard search engines that produce single-paragraph summaries, STORM simulates a collaborative expert panel to research complex topics thoroughly and assemble referenced research dossiers.
STORM operates via a two-stage cognitive pipeline: Pre-writing (discovering multiple perspectives, simulating expert questions, and gathering live web evidence) and Writing (organizing outlines, drafting sections, and verifying source citations). Researchers and professionals can run STORM locally or via the hosted web portal to generate 2,000+ word referenced reports on scientific, economic, or technical topics in minutes.
Enter a complex topic or research prompt.
STORM autonomously generates diverse expert personas and conducts targeted web searches.
The system gathers cross-referenced citations and synthesizes a structured outline.
Exports a full-length, formatted article with inline references.
Capabilities & Features
Common Use Cases
Generating referenced literature reviews and domain overviews
Synthesizing market research reports with multi-angle perspective analysis
Automating comprehensive fact-checked background dossiers on emerging tech
Frequently Asked Questions
How does Stanford STORM work?
STORM uses multi-perspective question asking to simulate panel interviews, retrieve diverse web sources, and synthesize verified, referenced articles.
Free Plan
100% free open-source research tool and hosted academic demo by Stanford University.
Paid Plan
No paid plans; BYOK (Bring Your Own Key) for self-hosted instances.
Direct link · Verified & reader-supported
Pros & Cons
Simulates expert perspective questions to discover non-obvious sub-topics
Rigorous inline citations linking directly to verified source URLs
Completely open-source Python codebase developed by Stanford University
In-depth research runs can take 2–5 minutes per comprehensive report
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