Date: August 19, 2026

PODScast: PODS-Structured Integrity Data – The Fast Lane for Pipeline AI/ML
In collaboration with Geonamic

Join us on August 19 for a new PODScast exploring how PODS-structured integrity data can support AI/ML initiatives in pipeline systems.

Pipeline operators today are data-rich but often insight-poor. Decades of integrity and asset data—especially high-value inspection data such as ILI—are frequently underutilized due to fragmented systems and manual analysis workflows. At the same time, AI/ML initiatives demand structured, high-quality data to deliver meaningful results.

This PODScast explores how the Pipeline Open Data Standard (PODS) provides a standardized, enterprise-grade data foundation purpose-built for pipeline operations. By organizing assets, inspections, welds, anomalies, and repair data into a consistent relational framework, PODS enables efficient data integration, improves data quality, and significantly reduces preparation effort for analytics.

We will demonstrate how PODS-structured data accelerates AI/ML readiness and supports advanced integrity use cases, including multi-run anomaly matching and predictive corrosion growth modeling. The session will also highlight how operators can transition from reactive, periodic reviews to proactive, predictive integrity management.

Join Geonamic to learn how structured integrity data unlocks scalable AI/ML, enhances decision-making, reduces risk, and drives more efficient and reliable pipeline operations.