"What I love about Sematic is that it's just Python. It's easy to implement with existing code, but also encourages better project design and thinking about the data being passed between steps.

It saves me a couple of hours every time I run the pipeline, which allows me to experiment more, and get better results."

"Sematic gives us unparalleled visibility into our ML pipelines (artifacts, logs, errors, source control, dependency graph, etc.) while keeping the SDK and GUI simple and intuitive.

It provides just the right level of abstraction for ML engineers to focus on business logic and leverage cloud resources without requiring infrastructure skills.

Sematic is the kind of pipelining tool used by ML teams at Uber, now available to Voxel and everyone else."

"Sematic is simple but powerful. In a few minutes I was able to get a template pipeline running, and tailor it to my specific needs and view everything in a surprisingly informative, straightforward UI.

The level of debugability but scalability that Sematic provides is awesome; it is barely opinionated (just add a function decorator) but hugely flexible.

I could easily see it become a standard tool for Machine Learning orchestration, pipelining, and even scaling."