Machine Learning for Large Scale Code Analysis

Code as Data

Turn your code into actionable insights

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Machine Learning on Code

Empower your Developers with Assisted Code Review

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NewAnnouncing Public Git Archive!

Why source{d}

Save time, improve your codebase quality,
and get actionable insights


Faster retrieval and analysis of your source code improving the efficiency of your engineering organization so you can always ship on time.


Improve the quality of your codebase with better Testing and QA, detecting potential defects and similar or duplicate code.


All your codebases in a single place coupled with powerful analytics tools to gain actionable insights for your teams and business.

How it works

source{d} powers Code as Data and
Machine Learning on Code

What you get?

source{d} Engine and source{d} Lookout

source{d} Engine

Code as Data

Leverage the source{d} Engine to turn your source code across versions into actionable data & business intelligence.


  • Source code retrieval and unification
  • Language classification and parsing
  • SQL interface for easy querying of repositories
  • SDK for analysis beyond SQL

Use cases

  • Code exploration
  • Engineering Dashboards
  • Business Intelligence
  • Security vulnerability detection
  • Continuous code quality
  • and much more!

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source{d} Lookout

Machine Learning on Code

Distill all the knowledge from your code base to assist engineering teams to review code faster while missing fewer mistakes.


  • Inferred style guides
  • Naming suggestions
  • Common bug detection
  • Performance bottlenecks identification
  • Security vulnerabilities
  • Suspicious code indicators
  • Language agnostic assisted coding

Use cases

  • Code reviewer attention guide
  • Comment suggestion
  • Author pre-check tool
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We believe in Open Source and Open Science

At source{d} we are creating a suite of Open Source tools enabling "Code as Data" and "Machine Learning on Code". We are also great believers in Open Source and its philosophy.

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Trusted by top engineers at world leading companies

Jessie Frazelle Microsoft

Jessie Frazelle Software Engineer at Microsoft

source{d} is not only a great open source citizen with projects like gitbase and their collection of research papers on machine learning for code. They have the expertise and user experience skills to make something that will be truly revolutionary to the way developers interact with code.

Jérôme Petazzoni Docker

Jérôme Petazzoni Software Engineer at Docker

The folks at source{d} are doing neat deep learning on source code history; and, of course, it's in Docker containers🐳.

Latest Updates

Announcing public git archive

Announcing Public Git Archive, the largest dataset of git repositories in the world

Francesc Campoy
Detecting licenses in code with go and ml

Detecting the license of an open source projects is harder than…

Vadim Markovtsev
Calling C functions from BigQuery with…

As part of our experimentations at source{d}, we decided to…

Francesc Campoy

Try source{d} Engine today

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