Tangle

Open-source ML experimentation platform with visual pipelines and smart caching.

Open Source Coding & Development
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What is Tangle?

Tangle is an open-source, platform-agnostic ML experimentation platform maintained by Alexey Volkov with Shopify as its initial sponsor. Users drag components onto a canvas and wire them into pipeline graphs that run locally or in the cloud, while a caching layer reuses previously executed steps so iteration stays fast and cheap. All runs are stored permanently, making pipelines reproducible years later, and any containerized CLI program can serve as a component.

Key features

  • Drag-and-drop visual pipeline canvas with auto-layout
  • Caching layer that skips or reuses already-executed steps
  • Permanent run storage: graphs, components, and logs kept forever
  • Open-source Tangle CLI and Tangent agent skills (Apache 2.0)
  • Any containerized CLI program works as a pipeline component
  • Component generation from Python source
  • Published component library and semantic component search
  • Pipeline validation and YAML export

Pros

  • Full reproducibility: every run, graph, and log stored indefinitely
  • Caching makes experimentation loops fast and cheap
  • Truly open: Apache 2.0, developed in the open on GitHub with PRs welcome

Cons

  • Niche focus on ML experimentation, not general-purpose coding
  • Visual canvas approach may not suit code-first teams
  • Younger ecosystem than established tools like Airflow or Kubeflow

Tangle at a glance

PricingOpen Source
CategoryCoding & Development
Platformsweb, api
Official websitetangleml.com
ml-experimentationopen-sourcemlopspipeline-builderagentic-codingreproducibilityvisual-editorcli

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Tangle FAQs

What is Tangle?

Tangle is an open-source, platform-agnostic ML experimentation platform maintained by Alexey Volkov with Shopify as its initial sponsor. Users drag components onto a canvas and wire them into pipeline graphs that run locally or in the cloud, while a caching layer reuses previously executed steps so iteration stays fast and cheap. All runs are stored permanently, making pipelines reproducible years later, and any containerized CLI program can serve as a component.

What are the main features of Tangle?

Tangle offers Drag-and-drop visual pipeline canvas with auto-layout, Caching layer that skips or reuses already-executed steps, Permanent run storage: graphs, components, and logs kept forever, Open-source Tangle CLI and Tangent agent skills (Apache 2.0), Any containerized CLI program works as a pipeline component, Component generation from Python source, Published component library and semantic component search and Pipeline validation and YAML export.

How much does Tangle cost?

Tangle is open source, so the software itself is free to download, use and self-host. Your only costs are the infrastructure you run it on and any paid services you connect to it.

What are the pros and cons of Tangle?

Strengths of Tangle include Full reproducibility: every run, graph, and log stored indefinitely; Caching makes experimentation loops fast and cheap; Truly open: Apache 2.0, developed in the open on GitHub with PRs welcome. On the downside, Niche focus on ML experimentation, not general-purpose coding; Visual canvas approach may not suit code-first teams; Younger ecosystem than established tools like Airflow or Kubeflow.