When something goes wrong, VROC doesn’t just raise an alert—it shows why.
Every prediction automatically captures the factors that contributed to an issue, giving engineers clear, ranked insights into what changed and where to focus.

Alarms tell you something’s wrong—not why

In most industrial environments, identifying the root cause of an issue is time-consuming and uncertain. Engineers must sift through trends, compare signals, and rely on experience to piece together what happened—often after the impact has already occurred.

 

With increasing data volumes and system complexity, traditional root cause analysis becomes slower, more reactive, and harder to scale.

 

Root cause insights, captured automatically

VROC embeds root cause analysis directly into every prediction. As soon as a deviation or failure risk is detected, the platform automatically identifies and records the contributing factors—down to individual sensor level.

 

Instead of searching through data, teams can immediately drill into an event and see the most influential signals, ranked by their impact.

How it works

Automatic contributor tracking

Every prediction logs the variables that influenced the outcome—without manual investigation.

Ranked contributing factors

Signals are prioritised based on impact, helping teams focus on what matters most.

Sensor-level transparency

Drill down into individual data points to understand exactly what changed.

Event-based analysis

Investigate issues in context, not in isolation—across time, assets, and processes.

Why it’s different from traditional RCA

• Root cause insights are captured automatically—not reconstructed after the event 

• Contributors are prioritised—not buried in data 

• Faster troubleshooting with clear, explainable evidence 

• Engineers stay in control, with insights they can validate and act on

 

From “something’s wrong” to “here’s why”

The AI explains its thinking—showing which signals mattered most—so teams can move from identifying a problem to understanding its cause in minutes, not hours or days.

 

Operational impact

• Faster root cause identification 

• Reduced downtime and production losses 

• Improved decision-making under pressure 

• Greater confidence in operational insights

 

Part of a broader industrial AI approach

VROC’s AI-based root cause analysis forms part of our broader approach to industrial AI.

Deviation Management → Detect issues earlier 

Time to Failure Prediction → Predict when failures will occur 

Solutions → See how this scales across operations

 

Stop searching for answers – start seeing them

Discover how VROC helps your team move from detection to understanding—faster and with greater confidence.

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Operate with clarity. Perform with confidence

Gain real-time visibility, predict failure earlier, optimize performance, and take control of your operations with VROC’s integrated solutions.