TOPON-PREDLY
See the failure
before it happens.
Predictive maintenance for hydrogen energy equipment. TOPON-PREDLY monitors electrolyzers, compressors, dispensers, and storage in real time, and tells you a component is failing weeks before it does.
// The Problem
Unplanned downtime is expensive. Hydrogen makes it worse.
A failed compressor seal on a hydrogen fueling station can take the site offline for days. A dispenser outage during peak demand means lost revenue, safety incidents, and regulatory scrutiny. Most operators find out when something breaks - not before.
Reactive maintenance is the default
Most hydrogen operators rely on scheduled intervals or failure-triggered repairs. Neither approach accounts for real equipment degradation patterns or operating conditions.
Hydrogen failure modes are unique
Electrolyzer stack degradation, compressor seal wear, and dispenser valve fatigue follow physics that generic industrial monitoring tools were not built to understand.
ESG reporting has no single source
Green H2 production data, CO2 offset tracking, and audit-ready ESG metrics are scattered across vendor systems with no unified view for compliance teams.
// How It Works
Four layers from sensor to prediction
TOPON-PREDLY is not a generic anomaly detector. It is built on a physics-informed stack that understands why hydrogen equipment fails, not just when readings look unusual.
Sensor Ingestion
Connects to your existing sensors and SCADA systems via standard protocols. No rip-and-replace. Works with whatever instrumentation you already have installed.
Canonical Asset Model
Each device class - electrolyzer, compressor, dispenser, storage - is mapped to a standardized digital model that normalizes data across different vendors and configurations.
Failure Physics Library
A curated library of degradation physics per equipment class. Compressor seal wear, membrane fouling, valve fatigue - each failure mode has its own physics model, not a generic threshold.
Physics-Informed ML
Machine learning models constrained by the physics library. Transfer learning means the models work even with limited historical failure data from your specific equipment.
// What It Monitors
Built for hydrogen equipment, class by class
TOPON-PREDLY covers the full hydrogen value chain - from generation to end use. Each device class has its own named failure modes, not generic anomaly detection.
Electrolyzers
Compressors
Dispensers
Cryogenic Storage
Chillers
// Platform Screenshots
See the platform in action
All screenshots show simulated data from our live demo environment.
// Pilot Program
Start with a scoped pilot
We work with a small number of hydrogen operators and investors to validate TOPON-PREDLY against real equipment data. Here is what a pilot includes.
What a pilot includes
- Equipment review and sensor mapping session (30 min call)
- Custom asset model configuration for your device classes
- Failure physics library calibration for your operating conditions
- Live dashboard deployment with your simulated or real sensor data
- PHM scheduler setup and alert threshold configuration
- Green H2 and ESG reporting module activated
- 30-day monitoring period with weekly check-ins
- End-of-pilot report with failure predictions and ROI estimate
Best fit for: hydrogen fueling station operators, electrolyzer OEMs, green H2 project developers, and infrastructure investors conducting technical due diligence.
// HONEST STATUS: TOPON-PREDLY is in demo stage with simulated data; we are onboarding pilot partners now. The demo is live, the physics models are built, and the platform is ready for real sensor data. We are not in production with a paying customer yet - that is what the pilot program is for.
Ready to see it with your equipment?
Book a 30-minute call and we will walk through exactly how TOPON-PREDLY maps to your specific hydrogen assets and failure history.