A leading US retail organization with a large and diverse product portfolio, had long relied on a collection of fragmented data systems to manage its sales orders and inventory. Over time, what began as a manageable setup had grown into a web of inconsistent reports, scattered metrics, and limited cost visibility, making it increasingly difficult for the business to trust its own data….
Q1 2026 had it all , celebrations, a GPTW hat-trick, client wins, and impactful academia collaborations. It was a quarter packed with moments that made us proud.
Many organizations begin their AI journey with powerful ideas and impressive Pilot phase, but when data expands into petabytes, when latency requirements drop to milliseconds, and when deployment enters the labyrinth of enterprise security, the “lab-grown” AI often withers.
A leading retail organization successfully migrated its monolithic Matillion ETLworkloads from a constrained Azure Virtual Machine (VM) deployment to the elastic, modern Matillion Data Productivity Cloud (DPC). This strategic move, executed in partnership with Emergere Technologies, leveraged a hybrid architecture utilizing Azure Kubernetes Service (AKS) for containerized execution.
Managing customer relationships in supply chain operations demands precision and identifying untapped cross-selling opportunities across thousands of transactions can transform static buyers into high-value partners. However, legacy analytics often fail to uncover meaningful patterns at scale, leaving revenue on the table amid fragmented data and manual guesswork.