Data Observability

Monitor data at rest for ensure data is complete and fresh. Pre-configured monitors and machine learning frameworks are available out of the box providing immediate value to customers.

Data Volume

Machine learning based anomaly detection monitoring for missing data with automated root-cause analysis

Data Freshness

Machine learning based anomaly detection monitoring for stale data with automated root-cause analysis

The World’s Leading Companies Trust Pantomath

Rob Brichler - CTO @ Lendly

"Pantomath's end-to-end observability across the entire data stack has significantly reduced data downtime and increased trust in data at our company.”

Rick Huff - CIO @ Paycor

"We selected Pantomath due to its one-of-its-kind platform that auto-discovers our data assets, visualizing these relationships in real-time across our ecosystem. Pantomath provides end-to-end traceability, which enables our teams to focus on building new solutions instead of getting mired down in operational tasks. We believe Pantomath will enable significant productivity savings while ensuring our data is reliable and trustworthy."

Gary Meyer - Director of Data Management @ CNG Holdings

"Pantomath autonomously identified a critical data incident within a complex data pipeline used by thousands of our users. Thanks to Pantomath's data observability platform, our team was notified with a real-time alert and automated root cause analysis, enabling our team to resolve the incident without impact to end users."

Paul Bessire - Chief Data Officer @ Coterie Insurance

“Data reliability is a major issue for enterprise businesses and startups alike. Most successful businesses derive their advantages through data, making healthy data pipelines critical for success. Pantomath solves this problem head on through its innovative product."

Mark Knipfer - Senior Data Analyst @ Lendly

"Pantomath required zero setup! We had end-to-end cross-platform pipeline lineage and out of the box monitoring in minutes."

Automated data operations across your data stack

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