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
Andrew Connolly - Director of Platform Reliability @ WEX
"We start and end our day with Pantomath. The unprecedented visibility that Pantomath has given my team has significantly improved our efficiency.”
Sandy Steiger - Sr. Director of Advanced Analytics @ TQL
"I have the peace of mind that I won’t get a phone call in the middle of the night, and there is no need to sit on calls to manually troubleshoot and figure out what happened. We know what has broken, right away.”
Sarang Deshpande - VP of Data @ Franciscan Health
"If our CFO spots incorrect revenue reports, or clinical teams rely on outdated insights, that’s not just an inconvenience—it impacts patient care and operational efficiency. Pantomath is helping us shift from reactive problem-solving to proactive data management.”
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.”
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."
Mark Knipfer - Sr. Data Analyst @ Lendly
"Pantomath required zero setup! We had end-to-end cross-platform pipeline lineage and out of the box monitoring in minutes."
