MayimFlow Introduces First Leak Prediction for Data Centers
December 28, 2025
A new AI-driven monitoring platform promises to transform how data center operators manage one of their most persistent and costly risks: water leaks from cooling systems. Startup MayimFlow, founded by veteran infrastructure engineers, has launched a system designed to forecast leaks 24 to 48 hours before they occur, allowing for scheduled maintenance without disrupting critical compute workloads.
The platform represents a significant shift from reactive to predictive maintenance in an industry where cooling-related failures are a leading cause of unplanned outages. According to the Uptime Institute, the financial impact of such outages continues to rise, with a growing number incurring costs reaching six or seven figures. Beyond immediate repair bills, even short interruptions can trigger cascading effects, including lost transactions, breached service-level agreements, and lasting reputational damage.
MayimFlow’s technology employs rugged Internet of Things (IoT) sensors and edge-deployed machine learning to analyze high-frequency data on flow, pressure, temperature, and vibration within chilled-water loops, humidification lines, and heat-exchange equipment. By identifying subtle precursors to failure—such as pressure transients, micro-vibrations, or acoustic anomalies in valves—the system aims to detect issues like a failing gasket or fatiguing valve long before a leak manifests. Co-founder Khazraee stated that the models were trained on diverse data from industrial water systems, enabling them to recognize early warning signs like cavitation or mechanical seal degradation. This approach, he said, provides "meaningful lead time" for operators to schedule repairs, order parts, and intervene proactively.
The business case extends beyond avoiding downtime. Preventing leaks also mitigates secondary damage to servers, power distribution units, and raised floors, which becomes far more expensive once water begins to spread. Furthermore, the platform aligns with growing sustainability and regulatory pressures. With the AI boom driving up power and cooling demands, water conservation is increasingly critical. Proactively addressing leaks and makeup-water losses helps operators manage their Water Usage Effectiveness (WUE) metric. For large-scale providers operating on thin margins, even a fractional reduction in outage rates can significantly improve availability metrics. There is also an insurance dimension, as underwriters increasingly reward operators who implement predictive monitoring of critical systems with better policy terms.
While initially targeting data centers, MayimFlow’s roadmap includes expansion into hospitals, industrial facilities, and commercial buildings with critical pressurized water networks. The company, which integrates with existing building management systems, positions itself as an essential reliability tool for the AI era—a less glamorous but vital layer in the infrastructure stack focused on maximizing uptime and resource stewardship.
Source: findarticles
