Technology

Specialized agents powered by advanced ML.

Verolyze connects plant data, predictive models, expert reliability logic, and AI-assisted reasoning so teams move from raw signals to approved operational actions.

Agentic ML operating stack● From signal to action
01Data foundationSCADA, alarms, events, meters, maintenance and weather context.
02Predictive ML modelsThermal drift, peer deviation, anomaly progression and failure indicators.
03Reliability agentsExplain risk, collect evidence, recommend next action and create review notes.

Agent action example

A specialized agent reviews model evidence and prepares an action packet for the reliability team.

Risk classThermal
Model confidence91%
Next stepApprove

Agentic architecture

AI agents on top of operational intelligence, not beside it.

The agent layer uses the same telemetry, model outputs and expert reliability context to move from detection to recommended action.

AI reliability agent report across laptop and mobile
Observe

Normalize SCADA, alarms, events, meters and maintenance states into a reliability-ready data foundation.

Reason

Combine predictive models, peer comparison and expert rules to explain why a signal matters.

Act

Create an action queue, suggested inspections and reporting notes for the reliability team.

Model evidenceEvidencia del modelo

Models that reveal abnormal behavior before it becomes failure.Modelos que revelan comportamiento anormal antes de que se convierta en falla.

Predictive models compare expected behavior against actual operating conditions, flag drift, and help teams intervene before risk escalates.Los modelos predictivos comparan el comportamiento esperado contra las condiciones reales de operación, detectan desviaciones y ayudan a los equipos a intervenir antes de que el riesgo escale.

Predicted versus actual temperature model and MAPE by time period

Platform layers

Explore the intelligence pipeline.

Each layer preserves context and makes the next operational decision easier.

Data Foundation

Telemetry, alarms, events, meters, RTUs, substations, maintenance states, and technical documentation.

Predictive Models

Detect abnormal patterns in transformers, generators, gearboxes, inverters, strings, and fleet-specific components.

AI Copilot

Explain risk, summarize evidence, and recommend next actions in natural language.

Architecture

Built for mixed renewable environments.

Designed to sit above existing plant systems while turning heterogeneous data into a consistent reliability view.

Second-level SCADA integration

Connect plant, substation, RTU, meter, and monitoring data across multiple vendors and systems.

Operational risk reporting

Transform technical signals into concise priorities, evidence, and recommendations.

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