diff --git a/pages/querying/vector-search.mdx b/pages/querying/vector-search.mdx
index 50ce52e36..1e5ab1c62 100644
--- a/pages/querying/vector-search.mdx
+++ b/pages/querying/vector-search.mdx
@@ -160,6 +160,16 @@ for the metric is `l2sq` (squared Euclidean distance).
 | `sorensen`  | Sørensen-Dice coefficient                           |
 | `jaccard`   | Jaccard index                                       |
 
+### Cosine similarity
+
+You can calculate cosine similarity directly in queries using the `vector_search.cosine_similarity()` function. This is useful when you need to compute similarity between vectors without creating a vector index.
+
+{<h3 className="custom-header"> Usage: </h3>}
+
+```cypher
+RETURN vector_search.cosine_similarity([1.0, 2.0], [1.0, 3.0]) AS similarity;
+```
+
 ### Scalar type
 
 Properties are stored as 64-bit values in the property store. However, for efficiency, vector elements in the vector index are stored using 32-bit values by default.