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    1. Home
    2. Tools
    3. STORM
    STORM icon

    STORM

    Research Assistants

    AI-powered research tool that generates comprehensive Wikipedia-style articles from scratch using multi-perspective question asking.

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    At a Glance

    Pricing

    Free

    Free access to STORM research tool

    Engagement

    Available On

    Web

    Resources

    WebsiteGitHubllms.txt

    Topics

    Research AssistantsContent GenerationInformation Synthesis

    Alternatives

    ASTARudel AINotebookLM

    Developer

    Stanford OVALStanford Open Virtual Assistant Lab (OVAL) builds LLM-augmen…

    Listed Jan 2026

    About STORM

    STORM (Synthesis of Topic Outlines through Retrieval and Multi-perspective Question Asking) is an AI-powered research assistant developed by Stanford University that automatically generates comprehensive, Wikipedia-style articles on any topic. The system leverages large language models to conduct thorough research by simulating conversations between multiple AI personas with different perspectives, then synthesizes the gathered information into well-structured, citation-backed articles.

    Key Features:

    • Multi-Perspective Research - STORM simulates conversations between AI personas representing different viewpoints and expertise areas, ensuring comprehensive coverage of topics from multiple angles.

    • Automatic Outline Generation - The system creates detailed topic outlines before writing, organizing information hierarchically similar to Wikipedia article structures.

    • Citation Integration - All generated content includes proper citations and references to source materials, maintaining academic integrity and verifiability.

    • Wikipedia-Style Output - Articles are formatted in familiar Wikipedia style with sections, subsections, and organized content flow for easy reading and navigation.

    • Retrieval-Augmented Generation - STORM uses advanced retrieval techniques to gather relevant information from the web, ensuring articles are grounded in factual sources.

    • Interactive Research Process - Users can input any topic and watch as the system conducts research, asks questions, and builds comprehensive articles.

    Getting Started:

    To use STORM, simply visit the web interface and enter a topic you want to research. The system will automatically begin its multi-perspective research process, generating questions from different viewpoints and retrieving relevant information. Once the research phase completes, STORM synthesizes all gathered information into a structured article with proper citations. The entire process is automated, requiring no manual intervention beyond the initial topic input. Users can review the generated outline and final article, which includes references to all sources used during the research process.

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    Pricing

    FREE

    Free Plan Available

    Free access to STORM research tool

    • Multi-perspective research
    • Wikipedia-style article generation
    • Automatic citations
    • Outline generation
    • Web-based access
    View official pricing

    Capabilities

    Key Features

    • Multi-perspective question asking
    • Automatic outline generation
    • Wikipedia-style article synthesis
    • Citation and reference integration
    • Retrieval-augmented generation
    • AI persona simulation
    • Topic research automation
    • Structured content organization

    Integrations

    Web search APIs
    Large language models

    Reviews & Ratings

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    Developer

    Stanford OVAL

    Stanford Open Virtual Assistant Lab (OVAL) builds LLM-augmented cognition systems that combine the expressive language skills of large language models with the interpretability and reliability of software systems. Led by Professor Monica Lam, the lab creates AI assistants like STORM, WikiChat, and other open-source tools used by consumers, historians, and journalists. OVAL connects LLMs with databases, compilers, and executive functions to create trustworthy and helpful assistants.

    Read more about Stanford OVAL
    WebsiteGitHubX / Twitter
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