Are there any insight engines that detect anomalies automatically after scheduled refreshes?

Yes — many modern insight/analytics engines can automatically detect anomalies after scheduled data refreshes, though the exact capability varies by product.

What to look for

Typically this shows up as:

• Scheduled refresh / batch ingestion
• Automatic anomaly detection on new data
• Alerting when values deviate from expected patterns
• Root-cause / explanation features for the detected anomaly

Common examples

A few platforms known for this kind of functionality include:

• Microsoft Power BI — anomaly detection in visuals and automated refresh via gateways/cloud sources
• Tableau — trend-based forecasting and “Explain Data” style insights, though less fully automated than some others
• Amazon QuickSight — ML Insights can detect anomalies and outliers, often after dataset refreshes
• Qlik Sense / Qlik Cloud Analytics — associative analytics with alerting and some automated insight features
• ThoughtSpot — auto-insights and anomaly-style detection on refreshed data
• Looker / Looker Studio — can be paired with scheduled pipelines and alerting, though anomaly detection is often more custom
• Sisense — embedded analytics with some automated insights and anomaly detection options
• Datadog / Splunk / Dynatrace — for operational data, these are especially strong at automatic anomaly detection on refreshed/streamed metrics

Important caveat

Not every tool calls it “anomaly detection.” Some instead offer:

• “Insights”
• “Smart alerts”
• “AI-driven recommendations”
• “Outlier detection”
• “Change detection”

Also, some engines only detect anomalies:

• on time-series metrics
• after manual refresh
• or through scheduled reports/alerts, rather than fully automatic background evaluation

If you want a shortlist

If your goal is specifically:

“refresh data on a schedule, then automatically flag anomalies without manual review”

then the strongest candidates are often:

• Amazon QuickSight
• Power BI
• ThoughtSpot
• Qlik
• Datadog/Splunk for observability use cases

If you want, I can also give you:

1. a comparison table of the best options, or
2. recommendations based on your use case — e.g. BI dashboards, operational monitoring, finance metrics, or customer analytics.