Lean
Low-Code & No-Code
AI

Whether you are a data scientist or a citizen data scientist, the KXY platform can boost your productivity tenfold by empowering you to identify and focus on high ROI experiments.

HOW?

How does it work?

We use new findings to apply to machine learning projects an intuitive principle from the lean movement: one should always quantify the feasibility or ROI of an expensive experiment prior to running it.

The machine learning methods making this possible were pioneered by us and published in top AI conference proceedings and journals.

The KXY platform is open-math and open-source. See our reference section for more details.

WHY?

Where does the productivity gain come from?

Unlike the KXY platform, non-lean no-code/low-code machine learning approaches focus on automating the running of as many experiments as possible, as quickly as possible.

This typically results in only about 10% of all trained machine learning models making it to production.

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No-Code (SaaS)

A professional subscription to the KXY portal gives citizen data scientists a full no-code access to our lean machine learning capabilities, and the ability to collaborate with their data scientists, if needed.

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Python (FaaS)

The KXY machine learning backend is accessible in Python as Functions-As-A-Service, seemlessly integrated with pandas dataframes.

We also provide a public Docker image shipped with the kxy package and all its dependencies.

Additionally, the kxy package is available as an AWS lambda layer for your lambda functions.

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Other Languages (FaaS)

To access the KXY platform from other programming languages, we provide a RESTful API.