Focus on high tech.

Create eCharts components with Shimoku and Python.

Shimoku sponsors the legendary Aspar Team in MotoGP

We believe in a tool that allows anyone to create Machine Learning that can reach business users frictionlessly. In that pursuit we are driven by the following features to change the world

welcome to the new Data Product era‍That is why we thought of a unique architecture, one that would give me, and anyone else in the same situation, the autonomy a data specialist (data analyst, data scientist, data engineer, or some IT persona with an interest in analytics)

Data products and the data mesh importance has emerged as a consequence of a key factor: the increase in the demand for Artificial Intelligence in the past 5 years.

while working on data projects I was tired that I couldn't easily share Machine Learning insights that could boost my clients’ business performance without a full-stack IT team.I was tired of how slow it was to show data analytics to people in a professional way with a progressive-web app technology (PWA from now on).

It is common to hear that the real fight is data cleaning when developing a data product, because it takes about 80% of our time.

We, the data specialists, can do amazing things that rarely arrive at production level. It is like we have been unfinished as a workforce.

To build a data app one needs:‍The client tier, where the Front-End developer struggles to create the new charts the product demands;‍