From Any Quant Research
to Runnable Strategy

Upload any quantitative research — arxiv, journal, or internal,
and get a structured, reproducible implementation. Same day.

Get started

Product

Find research. Implement it.
Evaluate what works.

Explore a growing  Library of published research

  • Browse published research across arxiv, SSRN, and journals
  • Preview implementations before committing to a full run
  • Track what your team has already evaluated
Explore the Library

Turn analysis into actionable insights

  • Review the Research Report: results, methodology, reproducibility assessment
  • Compare implementations across different model runs
  • Export or fork the repository for further development
Explore the Workspace

How it works

From upload to working
implementation

01

Upload Your Paper

Upload a PDF or research document

02

Choose a Model

Select the model that best fits your analysis

03

Run & Review Results

Watch the analysis progress and explore the Research Report

04

Export

Access your GitHub repository and continue development

What you get

Three outputs. Every time.

Research Report

Review experiment results, assessments, and reproducibility insights in one comprehensive report

Reproduced Partial Not reproduced

GitHub Repository

Every implementation is stored in its own GitHub repository, ready to fork, modify, and maintain

MCP Integration

Fine-tuned AI models, accessible via MCP for your agent workflows

"url": "mcp.quantcode.ai"

Who it’s for

For teams where research
backlog moves faster than engineering capacity

Academic Researchers & Independent Researchers

Publish reproducible code alongside your research

Quants & Prop Researchers

Move from research to implementation without days of boilerplate engineering

Portfolio Managers

Publish reproducible code alongside your research

The next strategy starts
with research

Convert quantitative research into production-ready code

Get started