Kramp Transforms Business Operations Through Advanced Real-Time Machine Learning Analytics

"The real-time updates on order status have not only improved transparency but also helped to reduce the number of customer service calls." — Oliver Meisch, Manager of Business Intelligence, Kramp

Kramp, a leading agricultural parts distributor, needed to modernize its data infrastructure by moving from batch-dependent data warehousing to real-time cloud analytics on Google Cloud Platform and BigQuery. Their legacy migration solution was unreliable, causing data quality issues and heavy maintenance overhead.

Striim delivered real-time data integration connecting Kramp's diverse source databases (Oracle, Microsoft SQL Server, and PostgreSQL) to BigQuery with continuous, high-quality replication. This provided the fresh data foundation needed for forecasting and order management.

Key outcomes:

• Better customer experience: instant order status updates reduced customer service call volume and improved transparency
• Lower operational costs: automated order processing with minimal latency
• Improved business KPIs: fresh data access strengthened order processing and inventory management metrics
• Data reliability: flawless transfer accuracy boosted stakeholder confidence

"The real-time updates on order status have not only improved transparency but also helped to reduce the number of customer service calls." — Oliver Meisch, Manager of Business Intelligence, Kramp

Download the full case study to learn more.

Striim is the real-time data platform for enterprise AI. Striim unifies data from clouds, apps, and databases, protects data as it moves through the pipeline and delivers data in sub-second latency. The result is a trusted, integrated, real-time context layer to feed agents—all at enterprise scale.

Striim’s real-time context engine bridges the gap between enterprise systems and context-starved agents, powering enterprise AI with high availability, in-flight governance, and data integrity enterprises can rely on.

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