Anomaly detection is only useful if it happens fast. But for many industrial teams, identifying an anomaly is still a manual, multi-day process.

Let’s take a real example: a European energy company monitoring turbines across multiple facilities. The operations team suspected irregular vibrations in one site, but to confirm it, they had to submit a query to the data team, wait 48 to 72 hours, and then interpret the result in a static report.

By the time they had their answer, the anomaly had already escalated.

The Latency Problem

Traditional workflows for anomaly detection look like this:

• Identify a signal manually
• Submit a query to the data team
• Wait 2–3 days for extraction, filtering, and charting
• Try to make a decision

In contrast, when that same company deployed Spocky, everything changed.

Spocky in Action: Instant Answers, Zero Friction

Instead of going through layers of systems and teams, the operations lead simply asked Spocky:

“Show me vibration anomalies in turbine 3 over the past 7 days.”

Within 3 seconds, Spocky returned:

• A time series chart highlighting outliers
• A textual summary explaining where and when the anomalies occurred
• Suggested next steps based on historical patterns

Why It Matters

With Spocky:

• The ops team identified the anomaly before it escalated
• They asked three more follow-up questions on-the-fly
• The root cause was pinpointed and fixed within a day

Most importantly, anomaly detection became reactive—and even proactive—instead of delayed and retrospective.

The Future of Anomaly Detection Is Conversational

When detection happens in seconds—not days—industrial companies move from firefighting to foresight.

Spocky makes this possible by removing the waiting, the intermediaries, and the complexity. And that means safer operations, faster resolution times, and fewer surprises.

Because in Industry 4.0, every second counts.