MayimFlow
MayimFlow provides predictive liquid-risk intelligence for AI data centers and critical infrastructure, using AI to learn each cooling loop's normal behavior and flag early warning signs of failure 24–72 hours before a leak occurs. The platform ingests pressure, flow, vibration, and water-chemistry signals from existing BMS, SCADA, and DCIM systems or optional clip-on sensors, then computes a live risk score and predicted time to failure for every loop. It is read-only by default, so it never changes control settings, and supports CDUs, cold plates, immersion cooling, and facility water loops.
- Artificial Intelligence
- Internet of Things
- Data & Analytics
- Software Only
Funding
Raised to date
$120KRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Founder details are not available yet.
Product
Problem
Liquid damage is more than twice as likely as fire to disrupt data center and industrial operations, yet conventional leak cables, spot sensors, and shutoff valves only react after liquid has already escaped. By the time an alarm sounds, water is on the floor, equipment is damaged, and costly downtime has begun—as seen when a single leaking pipe took a Google Cloud region offline for over a day.
Solution
MayimFlow provides predictive liquid-risk intelligence that learns how each cooling loop should behave and flags abnormal patterns 24–72 hours before failure. The platform ingests pressure, flow, vibration, and water-chemistry signals from existing BMS, SCADA, and DCIM systems or from optional clip-on sensors, then computes a live risk score and predicted time to failure for every loop. Its AI layer detects anomalies, traces the signal back to the likely component, reads thermal and camera images for wet or hot spots, and recommends the next repair action. Ranked alerts and repair tickets reach the right person via dashboard or phone, enabling teams to fix problems in a planned maintenance window instead of during an emergency. The system is read-only by default, so it never changes control settings until a team decides it should, and it supports CDUs, cold plates, immersion cooling, and facility water loops.
Target Audience
Primary customers are AI data center operators managing liquid-cooled racks, CDUs, and facility water loops, as well as utilities, hospitals, commercial buildings, and manufacturing sites with critical liquid systems.
Features
- AI models learn each liquid system's normal rhythm using pressure, flow, vibration, conductivity, pH, and thermal imaging signals
- Live risk score and predicted time to failure displayed for every loop, with the most urgent repair ranked at the top
- Clip-on sensors for vibration, pressure, ultrasonic flow, conductivity, pH, and thermal imaging fill gaps where existing data is unavailable
- Integrations with PLCs (Schneider Electric, Siemens, Allen-Bradley, Beckhoff, Opto 22, Phoenix Contact, WAGO), BMS, SCADA, DCIM via API, and weather services
- Read-only deployment requiring no control changes, with a typical 2–4 week rollout from kickoff to live monitoring
- Data encrypted in transit and at rest, with facility data owned by the customer and exportable or deletable on request