Case Study


Sportisimo uses a demand prediction system based on data science processes, reducing the labour-intensity of warehousing operations by 10%. Our simulations further showed that, when applied in stores, demand prediction had the potential to increase revenues by several percentage points.

Mall Group

We helped Mall Group to transform itself a data-driven company in which hundreds of people make data-driven decisions. Thanks to this, they now have a detailed overview of the profitability of products and the performance of the business as a whole.

Witty Trade

From part-time manual work in Excel to a comprehensive, automated BI solution thanks to Revolt BI.

Škoda Auto

Revolt BI helps the largest company in the Czech Republic to create a solution find items in warehouses and increase the efficiency of the warehouse procurement process.

Pietro Filipi

Our intelligent replenishment solution using Bl helped Pietro Filipi to save on a significant proportion of logistical costs and increase sales thanks to the improved availability of goods in stores.


Gathering and categorisation of 4.5 million car adverts from all over Europe every day thanks to Revolt BI.

Pet center

Increased efficiency, cost savings, better decision-making and improved user competence. With our assistance, PetCenter became a company where decisions are made based on data.


How did we help STOCK Plzeň-Božkov to improve its decision-making processes and operational efficiency? All we had to do was standardise data for reporting and proactively maintain the pipeline.