Outerbounds simplifies ML workflow management with integrated tools for orchestration, compute, and deployment.

Built for ML: A Specialized Alternative to Dagster

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Join our office hours for a live demo! Whether you're curious about Outerbounds or have specific questions - nothing is off limits.

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From Data Pipelines to ML Pipelines: Outerbounds Does It All

Dagster is a powerful data orchestration tool, but Outerbounds is purpose-built for machine learning. With native compute management, automatic versioning, and event-driven ML workflows, Outerbounds simplifies and scales your pipelines from experimentation to production. Replace complexity with a unified platform designed for data scientists.

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ML-Specific Tools

Tailored for Machine Learning

Outerbounds offers experiment tracking, model versioning, and deployment automation alongside orchestration, providing a complete ML solution out of the box.

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Simplified Workflow Management

Python-First, No Overhead

Define ML workflows in Python with no additional setup. Outerbounds eliminates the need for complex configurations or general-purpose abstractions.

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Built-In Compute Management

Scale Seamlessly Across Clouds

Outerbounds manages and optimizes compute resources for ML workloads, ensuring effortless scaling across AWS, GCP, Azure, and on-prem environments.

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Cost-Optimized and Scalable

ML Workflows Without Waste

Track and optimize cloud spend specifically for ML workflows with built-in tools that maximize efficiency while minimizing cost.

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Start building today

Drop in any Friday at 9am PT for an open Q&A with our team. Whether you're curious about Outerbounds or have specific questions — nothing is off limits.

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Trusted by the best

Been using metaflow for a while now, and love it. At its best, it hugely speeds up our development cycles
Harvey Pratt
Chief Executive Officer
Decoration