%20(1).avif)
.png)
Built for ML: A Specialized Alternative to Dagster
Start building today
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.
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.
%20(1).avif)
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.
%20(1).avif)
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.
%20(1).avif)
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.
.avif)
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.
%20(1).avif)
Trusted by the best
.png)
