diff --git a/_source/_data/toc.yml b/_source/_data/toc.yml
index 213a5c09f..c4881c633 100644
--- a/_source/_data/toc.yml
+++ b/_source/_data/toc.yml
@@ -339,6 +339,8 @@ firstLevel:
       url: /user-guide/cloud-siem/manage-feeds.html
     - title: Select dashboards for your Cloud SIEM Summary page
       url: /user-guide/cloud-siem/select-dashboards.html
+    - title: Anomaly detection
+      url: /user-guide/cloud-siem/anomaly-detection.html
 
 
 
diff --git a/_source/user-guide/cloud-siem/anomaly-detection.md b/_source/user-guide/cloud-siem/anomaly-detection.md
new file mode 100644
index 000000000..ebd034b14
--- /dev/null
+++ b/_source/user-guide/cloud-siem/anomaly-detection.md
@@ -0,0 +1,23 @@
+---
+layout: article
+title: Anomaly Detection
+permalink: /user-guide/cloud-siem/anomaly-detection.html
+flags:
+  logzio-plan: pro
+tags:
+  - logz.io-security
+  - siem
+contributors:
+  - hidan
+---
+
+
+Logz.io's **Anomaly detection** provides advanced analytics, helping you engage a more predictive approach toward your data. It applies machine learning and artificial intelligence to identify performance issues before they impact customer experience or even appear in production.
+
+By identifying data and events not aligned with your data's "normal behavior, " we can build a known, acceptable patterns model by utilizing historical telemetry data. Then, Logz.io queries data to locate and score the severity of anything that looks unusual.
+
+Anomaly Detection will surface critical health and performance issues that might have otherwise gone unseen and reduce the time needed to prioritize and investigate pressing alerts. These issues are then translated into dedicated alerts and visualizations for additional investigation.
+
+Instead of using the common monitoring approach of setting thresholds to look for specific issues, Logz.io's Anomaly detection lets you build a model and trend behavior to pinpoint the "unknown unknowns" – those scenarios most likely to catch them off guard when resulting in a production issue.
+
+###### To get started with Anomaly detection and for any additional info, contact your account executive or contact [Logz.io's support team](mailto:help@logz.io).
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