diff --git a/solutions/search/vector/knn.md b/solutions/search/vector/knn.md
index 1458fd5f03..570468338d 100644
--- a/solutions/search/vector/knn.md
+++ b/solutions/search/vector/knn.md
@@ -49,7 +49,7 @@ The default type of {{es-serverless}} project is suitable for this use case unle
 Refer to [](dense-vector.md#vector-profiles).
 :::
 
-## kNN search methods: approxiamte and exact kNN [knn-methods]
+## kNN search methods: approximate and exact kNN [knn-methods]
 
 {{es}} supports two methods for kNN search:
 
@@ -1224,7 +1224,7 @@ This example will:
 * Search using approximate kNN for the top 100 candidates.
 * Rescore the top 20 candidates (`oversample * k`) per shard using the original, non quantized vectors.
 * Return the top 10 (`k`) rescored candidates.
-* Merge the rescored canddidates from all shards, and return the top 10 (`k`) results.
+* Merge the rescored candidates from all shards, and return the top 10 (`k`) results.
 
 #### Additional rescoring techniques [dense-vector-knn-search-rescoring-rescore-additional]