Overview

Hyperresearch is an agent-driven research knowledge base that transforms large language models like Claude into powerful, autonomous research agents. It automates the entire deep research process, from collecting and synthesizing web data to generating comprehensive, adversarialy-audited reports. Every piece of information encountered is stored in a persistent, searchable vault, ensuring that each research session benefits from the knowledge gained in previous ones, creating a continuously improving and intelligent research ecosystem.

Key Features

• Automated Deep Research Pipeline: A sophisticated 16-step pipeline meticulously guides agents through decomposition, multi-perspective search, contradiction analysis, in-depth investigation, synthesis, and adversarial auditing.
• Adversarial Auditing & Verification: Reports undergo rigorous validation, including citation verification to ensure sources genuinely support claims, independence audits to prevent syndicated content from skewing results, and adversarial critiques to identify weaknesses.
• Persistent, Searchable Knowledge Vault: All research sources are stored in a markdown-plus-SQLite vault. This persistent storage allows for intelligent reuse of existing information, significantly speeding up future research and ensuring continuity.
• Handling Paywalled Content: Hyperresearch actively seeks open-access versions of paywalled papers and transparently discloses any substitutions, ensuring comprehensive data even when access is restricted.
• Resilient and Scalable: Runs are resumable, allowing interrupted research to pick up exactly where it left off. The system scales from quick surveys to extensive dissertation-length projects, adapting its pipeline and resources accordingly.
• Configurable Tiers and Gears: Research depth and scope are adjustable through "tiers" (light, full, dissertation) and "gears" (controlling source targets, depth, and word counts), allowing for tailored research efforts.
• Authenticated Crawling: Securely access content from sites requiring login, such as LinkedIn and Twitter, directly within your research workflow.
• Quality-Ranked Sources: A persistent quality_score for each source, derived from type, utility, citation authority (including retraction flags), and vault PageRank, ensures that the most reliable information is prioritized.

Typical Use Cases

• Academic and Scientific Research: Generate in-depth reports, literature reviews, and argumentative analyses on complex topics, supported by verified sources and adversarial checks.
• Market Intelligence and Competitive Analysis: Gather comprehensive insights into market trends, competitor strategies, and industry landscapes, with automated synthesis of diverse web data.
• Journalism and Investigative Reporting: Surface hidden connections, uncover overlooked details, and build robust case files with the aid of an agent that never discards information.
• Policy Analysis and Strategy Development: Synthesize evidence, identify expert disagreements, and build well-supported arguments for policy proposals or strategic decisions.
• Personal Knowledge Management: Continuously build and refine a personal research library that grows smarter with every use, making information retrieval and synthesis seamless.
• Content Generation: Produce structured, well-researched articles, whitepapers, and reports, leveraging the system's ability to draft and synthesize information from a vast corpus.