Craig Scientific LLC

Beyond search.

PhD-level research.
Hours, not months.

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See how it works ↓

Architecture based on state-of-the-art multi-agent systems research
Scaling Agent Systems • Kosmos Research

The full research loop.

Literature analysis. Experimental design.
Validation. Complete provenance.

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Iterative Deep Dive

Explores citation networks, identifies gaps, and loops until convergence.

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Experimental Design

Designs and runs computational experiments to test hypotheses and fill knowledge gaps.

✓

Full Provenance

Every claim traces to a DOI with exact quote, or an experiment with reproduction code.

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Quality Control

Multi-stage AI peer review validates every result before you see it.

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Publication-Ready

LaTeX papers, figures, and complete reproduction packages.

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Full Control

Watch in real-time. Intervene, guide, or approve at any stage.

Designed to converge.

Traditional AI retrieves and summarizes.
Craig researches.

Traditional AI

✗ Retrieve → Summarize → Output
✗ Single-pass extraction
✗ "Trust the AI"
✗ Literature review only
✗ No quality control
✗ Black box

Craig

✓ Iterative convergence loops
✓ Citation-recursive deep dive
✓ DOI + exact quote + confidence
✓ Designs & runs experiments
✓ 6 AI peer reviewers
✓ Full transparency, intervention

What you get.

Reproducible research outputs.
Complete provenance tracking.

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Experimental Plots

Publication-ready figures generated automatically

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Provenance Chain

Every claim traced to source with exact quote

Claim: "Transformer attention is O(n²)"

DOI: 10.48550/arXiv.1706.03762

Quote: "The complexity of self-attention is O(n²·d)"

Page: 5

Confidence: 0.92

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LaTeX Output

Academic writeup with proper structure and citations

\documentclass{article}
\begin{document}
\title{Research Findings}
\section{Introduction}
  Based on analysis of 147 papers...
\section{Methods}
  \cite{doi:10.48550/arXiv.1706.03762}
\end{document}

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Research Reports

Complete summary of research process and findings

Papers analyzed 147
Claims extracted 89
Hypotheses tested 3
Experiments run 13
Full reproduction package included

Built by researchers.

Our mission: accelerate scientific discovery by automating the full research loop.
Transparent. Reproducible. Rigorous.

Rye Howard-Stone, PhD

Founder & Principal Investigator

• PhD in Computational Biology, UConn (2025)
• NSF PaCE Scholar
• Published bioinformatics tools (AmpliconHunter, MHASS)
• Four peer-reviewed publications in computational biology

Ion Măndoiu, PhD

Advisor & Co-Principal Investigator

• Professor, Computer Science & Engineering, UConn
• 6,400+ citations in computational biology
• 100+ publications in bioinformatics and genomics
• Author of textbooks on NGS data analysis and bioinformatics algorithms