Information Technology
Use Case:

How Kineo Achieves Business Goals with Flyte™

Berlin-based Kineo provides AI solutions to clients in many industries. To deliver those solutions efficiently at scale, Kineo had to solve workflow challenges from its Kubeflow orchestration platform: lack of support for local execution, time-consuming code conversions from Jupyter Notebook to pipeline, and limited ML type support.

“Just this conversion of notebook code to pipeline code was taking a lot of a lot of time, doing really simple, stupid stuff like if-else statements and loops,” said Jan Fiedler, MLOps engineer at Kineo. “It was not like learning a new language, but it took us time.”

These pain points hindered Kineo’s data scientists and increased operational costs and prompted the company to seek a more efficient orchestrator. 

Flyte stood out for its seamless creation of pipeline code, automated testing capabilities and a rich set of components to extend its functionality. By streamlining workflows, Flyte reduced the cost of Kineo’s AWS base operations by 50%.

Meanwhile, the ability to develop locally with Flyte lowered Kineo’s cloud costs even more. Two weeks of data pipeline development fell from $160 to just $39 — a 70% reduction.

Fiedler credited the Flyte community with helping get Kineo up and running quickly. “It’s amazing. I think we figured out how to deploy Flyte in a couple of weeks, really, but this could only happen because, if we asked a question of the Flyte community, we could receive the answer in a couple of minutes.”

Discover the full story in our detailed case study. Download the PDF now.