ENERGY
From fragmented fleets
to unified reliability.
Anticipate failures across dispersed wind, solar, hydro, and grid assets — without adding headcount at every site, and without relying solely on your equipment manufacturer's account of what went wrong.
monom unifies SCADA, historian, and condition-monitoring data from every generation type into one contextualized layer, and pairs it with expert-validated AI — built for utilities and IPPs that already have sensors and systems in place and need the intelligence layer on top, not a rebuild.
30+ years of industrial expertise
80% reduction in diagnosis time
Sensor-agnostic deployment
THE CHALLENGE
Without a unified view across fleets, energy operations lose reliability — and negotiating power.
Geographically dispersed assets stretch your teams thin.
Wind and solar fleets spread across hundreds of kilometers make on-site response slow and expensive — you can't have a technician everywhere at once.
OEM diagnoses leave you at a disadvantage in warranty disputes.
Without independent condition data, you depend entirely on the turbine or equipment manufacturer's account of what failed and since when — weakening your negotiating position on warranty claims.
Every unplanned outage threatens grid reliability and revenue.
Rising demand from EVs and data centers, plus tightening interconnection and safety requirements, leave zero room for unplanned downtime.
Fragmented data across generation types blocks a fleet-wide view.
Wind, solar, hydro, and thermal assets each report through different SCADA, historian, and CMS systems, making fleet-wide prioritization guesswork.
Alert fatigue erodes trust in the tools you already have.
Teams drowning in false positives from legacy condition-monitoring systems eventually stop reacting to them.
Retiring reliability experts take decades of knowledge with them.
Institutional knowledge of turbine, generator, and grid-asset failure patterns walks out the door with every retirement — right when fleets are growing fastest.
THE PLATFORM
monom. From fragmented data to fleet-wide reliability.
The modular platform combining a multi-source Data Fabric, predictive maintenance, and expert-validated AI — purpose-built for utilities and IPPs managing dispersed, mixed-generation fleets.
INDUSTRIAL AI
Deploy in Weeks, Not Years
Our Industrial Data Fabric unifies OT and IT data from every generation type — wind, solar, hydro, thermal — automatically, with out-of-the-box connectors and a secure, ISO 27001 architecture your IT team will trust from day one.
PREDICTIVE MAINTENANCE
Independent Condition Data, Stronger Negotiating Position
Detect failure modes in turbines, generators, and grid equipment with data you own, not just what the OEM reports.
INTELLIGENT MAINTENANCE
From Raw Data to Bottom-Line Action
Go beyond simple alerts: our AI engine delivers clear root-cause diagnostics and recommendations prioritized by financial risk, then automatically creates work orders in your CMMS — cutting alarm-to-action time by up to 60% across every site in your fleet.
AGENTIC OPERATIONS
Expert AI Across Every Site, Not Just Headquarters
Pre-trained industrial agents diagnose root cause and prioritize maintenance across dispersed fleets in natural language — no training, no blank canvas.
Strengthen every link in your generation fleet
From the turbine to the boardroom, MonoM strengthens reliability, cuts costs, and keeps you grid-ready.
Independent condition monitoring
detect failures in wind, solar, hydro, and grid assets with data you control, not just what the OEM reports.
Optimized field dispatch
prioritize which site gets a technician first, based on real criticality, not geography or guesswork.
Single source of truth across fleets
vibration, SCADA, and history from every generation type on one screen.
OT and IT connected
integrate SCADA, historians, and GMAO/CMMS across every asset type in a governable, secure architecture.
Frictionless scalability
deploy predictive models site-by-site, fleet-by-fleet, with no vendor lock-in.
Guaranteed data security
ISO 27001-certified, with full operational traceability.
Contextualized data
move from raw sensor readings across dispersed assets to correlated, actionable insight in hours.
Advanced predictive analytics
anticipate turbine, generator, and grid-component degradation with industrial AI.
Smart alarms
contextualized alerts with diagnosis and recommended action, not just a threshold breach.
Controlled operating costs
reduce truck-rolls, emergency repairs, and downtime spend with real data-based decisions.
Clear ROI
evaluate the economic impact of every maintenance action and every warranty claim with traceable reporting.
Compliance and traceability
automate documentation for grid-code, ISO 55000, and decarbonization reporting requirements.
Trusted by the leaders shaping the future of energy
monom by Preditec organizes the X Foro de Fiabilidad y Mantenimiento Industrial — now in its 10th edition — the Spanish energy and industrial sector's own reference gathering for reliability and predictive-maintenance leaders.
30 years
Combined industrial reliability expertise
80%
Reduction in diagnostic time
10th
Edition of the industry's own reliability forum
Ángel García-Bombín
Industrial Digital Transformation Director
Sonae Arauco
We finally have full visibility into our asset health. Their virtual agents make everything transparent — from complex vibration analysis to the smallest detail — and the platform is incredibly intuitive.
Request a
personalized demo.
Discover how monom turns fragmented fleet data — across wind, solar, hydro, and grid assets — into frictionless, expert-validated decisions. Unify OT, IT, AI, and reliability workflows without ripping out what you already have. Your team sees impact from day one.
