David J. Phillips @davj / 2:30 PM PST • March 2, 2023
Today, DAGWorks launched on Y Combinator’s "Launch YC”
DAGWorks is building a more human capital efficient way for Data Science teams to build and maintain Machine Learning Pipelines, from creation to maintenance.
Founded by Stefan Krawczyk & Elijah ben Izzy, the pair built the self-service ML Platform for 100+ data scientists at Stitch Fix. They learned firsthand the challenges of building and maintaining ML pipelines across diverse modeling disciplines, as maintaining these pipelines becomes increasingly difficult as a team and codebase grows. The team's background includes building tools, quants, data & ML systems at Nextdoor, LinkedIn, and Two Sigma.
HOW IT WORKS
DAGWorks' solution is an open source SaaS platform for data science teams to build and maintain model pipelines. It integrates with as much of your existing MLOps and data infrastructure to the extent that you want.
Hamilton, DAGWorks' open source project that helps teams follow software engineering best practices, enables users to logically express actions, preventing vendor and infrastructure lock-in.
Using the DAGWorks Platform & Client, your Hamilton code runs on your existing infrastructure, providing out-of-the-box connectors to common systems, and post-execution insights.
The DAGWorks Platform serves as your ML Pipeline control plane. Building on a solid foundation that clearly decouples concerns, traditional issues with ML Pipelines can be avoided, enabling Data Science teams to work faster, more independently, and more effectively. The result? Greater human capital efficiency for ML projects.
Save time on managing ML ETLs and focus more on developing features and models. Eliminate the hassle of dealing with convoluted code, unclear data dependencies, and isolated knowledge silos.
LEARN MORE
Want updates? Follow them on Twitter: @DagWorks, @hamilton_os
Sign up for early access at www.dagworks.io (closed beta)
Star their open source project Hamilton on github and get started via tryhamilton.dev.
If you know of any larger organizations experiencing difficulties with their ML pipelines, particularly those with compliance or auditing needs, contact the DAGWorks team!
