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DeepCite

Why This is an Opportunity

Feynman (Claude Code for research) got 3.1K likes and 185K views in hours — proving massive demand for automated research with real citations. Academics, analysts, and founders all need this but Google Scholar plus manual reading takes days. The gap between what AI can produce and what researchers need is closable now with multi-agent architectures. An AI research agent that produces cited meta-analyses and can audit claims against source code.

Key Pain Points

  • You need a literature review on a niche topic and it takes 2 weeks of reading papers to write a decent one
  • ChatGPT gives you plausible-sounding claims with hallucinated citations that waste more time to verify than doing the research manually
  • You found a paper that claims X but have no easy way to check if their code actually supports the claim
  • You are a startup founder who needs to understand a technical domain fast but cannot afford a $500/hour domain consultant
Market Opportunity
AI-Powered Research Automation and Literature Review Software Market
Current Size (2026)
$1.8B
Projected (2036)
$13.9B
CAGR
22.7%
This market is projected to grow 672% over the next 10 years, reaching $13.9B by 2036.

Original Discovery

An AI research agent that takes any question and returns a fully cited meta-analysis within 30 minutes. You type a research question, select your rigor level, and the agent searches academic databases, preprints, and the open web. It synthesizes findings into a structured report with inline citations, methodology assessment, confidence levels, and a bibliography. It can also replicate computational experiments on cloud GPUs.

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