This is just the beginning

Seed Round Announcement, Major Product Releases, Content Rehaul

💸 Funding Announcement

Today, we have exciting news to share! ZenML got its first external investment. Crane from London is leading the 2.7m USD Seed round and Scott Sage will support as a board member. The round is followed by AIX, a new AI-fund from Palo Alto, and notable business angels, AI researchers and entrepreneurs. We are more than happy as they have a great track record, especially in MLOps as they also invested in H2O.ai, Hugging Face, and Weights & Biases. We will introduce everyone individually throughout the upcoming months. Read more here in our official press release. We also wrote a blog post from a personal perspective of how we came to the idea of ZenML.
(We normally don’t ask you to take any action in our Substack newsletter but this time you can support us for our Press Release on LinkedIn and Twitter. - Like, Comment, Share - Thank you! )

🔗 Major new features: Lineage Tracking and Kubeflow integration

With releases 0.5.4 and 0.5.5, we release two new features for ZenML: lineage tracking and the long-awaited Kubeflow (Pipelines) integration.

The new lineage tracking visualizer leverages the awesome Dash library to show how your pipeline runs develop over time. You can see which artifacts were cached, and trace back exactly what happened in the past. Check out a full example here.

The Kubeflow integration is a big milestone for us. There is a lot of talk of how difficult it is to run Kubeflow in production, and we always thought one of the biggest reasons is how difficult it is to get going with it FAST. The new integration lets you spin up Kubeflow locally with a simple command:

zenml stack up

And boom! You have a running Kubeflow Pipelines instance. It is equally easy to deploy a ZenML pipeline on it, with automatic containerization of your code! Give it a whirl now!

📽 First YouTube video - ZenML Demo

Just after we released the Kubeflow integration today, Hamza gave it a spin in a complete ZenML demo. See how easy it is to deploy and use Kubeflow locally with the right abstractions. Data scientists don’t even need to leave their Jupyter notebooks! I’ll let the video do its own talking:

🧐 PR rework of all user-facing content

You might have seen it already but we reworked all of our user-facing appearances for the big Press Release. We expect traffic and would like to catch everyone’s attention so that they try out ZenML right away! Now, the website landing page breaks down every step of ZenML as easily as possible. The user can now see at one glance how easy it is to bring a pipeline into production with just a few lines of code. We also refurbished our Docs and the Github Readme.

❤️ Another addition to the ZenTeam

We’re super happy to grow the core team with exceptional talent. Alexej just joined this month as Machine Learning Engineer. Besides growing ZenML, he also raises squirrels 🐿 as a Foster Parent. Welcome, Alexej!

We have ambitious goals, crazy ideas, and a huge backlog. For that, we’re still looking for more Machine Learning Engineers. We also need students who want to challenge the core team by using ZenML in real-world applications (ZenHacks). And, one of the most crucial positions is still open: our community-facing advicate - call it DevRel, Developer Advocate, or Tech Evangelist - we need another rockstar!

Find all the details on our hiring page and let us know if you know somebody!

🎙️Podcast “Pipeline Conversations”

Our podcast is lifting off - with the majority of listeners in the US! Alex published episode #2 with our first guest Noah Gift, the author of “Practical MLOps”. This week we will release the next version with an exciting guest and are already recording in parallel. It is very interesting to get insights from real MLOps practitioners - stay tuned!

It’s really exciting times! The seed round feels like the start of something big, and we can’t wait to share with you all how this develops. Until next time.

— Adam & Hamza