Who We Are
Hello, We’re Ploomber here to help you
Ploomber is the platform to accelerate your Data Science and Machine Learning workflows. From development to deployment - we got you covered. We help by making faster iterations from Jupyter or IDEs like VSCode/Pycharm/Rstudio/Spyder, caching the data pipeline tasks so the builds can be incremental, and making the work iterative, maintainable and easier to test. On top, it has native integrations with cloud providers like AWS and GCP and Ploomber also allows to deploy into multiple platforms like Airflow, Argo, Kubeflow and AWS Batch.
What We Do
Enable Best Practices
Bring software development best practices into data science while using your favorite editor (Jupyter, VSCode, PyCharm). Emphasize on testing and build modular pipelines
Short Learning Curve
Get started quickly. Build ML Data Pipelines in under 30 minutes. Keep working with the same tools you’ve been used to.
Faster Development Cycles
Iterate faster by skipping redundant computations. Debug a single pipeline task indtead of waiting long expensive database pulls.
Your code is being translated from the notebook so you can directly deploy it. Deploy without code changes into your production server, Kubernetes, AWS Batch, Airflow, or SLURM.
Our Main Vision And Mission
Both of us spent years working in the data space. Ido had been working at AWS leading data engineers and scientists, and constantly found that projects dedicated about 30% of their time just to refactor the notebook finished prototype into a production pipeline. Eduardo deployed production Machine Learning models and always found it annoying and wasteful to refactor his code when moving from notebooks into production frameworks like Airflow or Kubernetes. We were constantly struggling with existing MLOps tools that doesn’t solve our issues. We decided to bridge this gap and build our own framework. We came out with Ploomber to simplify our lives and bridge the gap between the Data and Ops teams.