Konverge AI

The client relied on a legacy business intelligence platform built on Palantir Slate that was designed for narratives rather than scalable analytics. The existing platform constrained reporting performance, interactivity, and speed to insight, limiting analytics adoption across the organization.

Konverge AI modernized the legacy BI platform by migrating it from Palantir Slate to Microsoft Fabric using a Medallion Architecture. The implementation established a scalable analytics platform that improved reporting performance and supported enterprise-wide reporting through Microsoft Fabric.

The client experienced fragmented data across multiple markets, making demand forecasting unreliable and contributing to overproduction, stockout losses, and inefficient production planning.

Konverge AI built an AI-driven customer data platform by integrating multi-source ETL pipelines and unified customer data models to support demand forecasting and planning. The solution incorporated advanced forecasting models across customer-product combinations together with promotions and product lifecycle management.

The client managed new social media data sources and feeds through an ad hoc registration process with fragmented ingestion pipelines across multiple platforms. This made onboarding new data sources inefficient and limited analytics across social media channels.

Konverge AI implemented a metadata-driven data ingestion and transformation framework on Databricks. The solution ingested data from multiple social media REST APIs and introduced a framework using Databricks Apps to register new data sources, creating a more consistent and scalable ingestion process.