Research code your team can build on
Check pipelines and analysis code for reproducibility before you reuse them, hand them over or publish with partners.
fix: Apply 1 AI-generated reproducibility fix
Fixes
Author-machine path in result code: /home/lab/counts.csv
Machine assumptions documented
@@ -8,3 +8,4 @@from pathlib import Pathimport pandas as pddf = pd.read_csv("/home/lab/counts.csv")ROOT = Path(__file__).resolve().parents[1]df = pd.read_csv(ROOT / "data/counts.csv")Your team reviews it never merged automatically
Reproducibility pays off beyond the paper
Reuse internal code
See which pipelines are documented and pinned well enough to build on.
Due diligence on code
Assess acquired or licensed research code before your projects depend on it.
Publish with partners
Give academic partners and journals code that meets their reproducibility expectations.
Smoother handovers
Findings and their fixes tell the receiving team what is missing.
What every check covers
Every check reviews materials and documentation for the level, with automation assessed beside it.
L1 · Materials available ·
- Code for each result is available
- Input data can be obtained
- Required software can be obtained
L2 · Workflow documented ·
- Dependencies and versions are listed
- The exact code version is identified
- Data sources have stable identifiers
- Data preparation steps are documented
- Code is linked to the paper’s results
- Instructions explain how to run the analysis
- Documented commands agree with the code
- Machine assumptions documented
Automation · separate assessment ·
- One command produces the results
- The software environment is pinned
- Input retrieval is automated
- Random seeds and variability are controlled
One plan for your whole team
Everyone works in the web app or from their AI agent, under one organization.
- One organization for your team
- Admins invite members
- A monthly budget in USD and member caps
- A usage report by member and project, with CSV
- Private repositories through the GitHub App
- Fixes opened as pull requests
Coming next
Coming soon- Execute: an opt-in deep check
- Integration API
Enterprise options on request: single sign-on, audit log export, EU‑hosted processing
Projects and reports stay private until you create a share link, publish a badge or open a pull request.
SecurityTalk to us about your team
Tell us about your team and your code, and we will put together a plan that fits.