Case Study: Knoldus builds a guided analytics forecasting platform with KNIME

How Knoldus enables efficient inventory forecasting with KNIME

Knoldus needed a better way to support sales and inventory forecasting in Consumer Packaged Goods, where stock decisions can strongly affect profitability. Traditional forecasting tools were too rigid, struggled to incorporate external and transactional data, and did not allow different models or parameters for different products and regions. The company turned to KNIME and its Analytics Platform to build a more flexible, guided forecasting approach.

KNIME and Knoldus created the Knoldus Forecasting Platform (KFP), a web application deployed on KNIME Server via the KNIME WebPortal. The solution let business users and data scientists collaborate on data ingestion, preprocessing, model selection, dashboards, and forecast review using statistical and machine learning models without heavy coding. The result was a configurable, faster forecasting workflow that improved collaboration and enabled more accurate, timely forecasts, though the case study does not provide specific numeric performance gains.

Knoldus