diff --git a/3.7/aql/functions-arangosearch.md b/3.7/aql/functions-arangosearch.md
index bd683476ff..a3d81a2609 100644
--- a/3.7/aql/functions-arangosearch.md
+++ b/3.7/aql/functions-arangosearch.md
@@ -457,7 +457,7 @@ Object tokens:
 
 - `{IN_RANGE: [low, high, includeLow, includeHigh]}`:
   see [IN_RANGE()](#in_range). *low* and *high* can only be strings.
-- `{LEVENSHTEIN_MATCH: [token, maxDistance, transpositions, maxTerms]}`:
+- `{LEVENSHTEIN_MATCH: [token, maxDistance, transpositions, maxTerms, prefix]}`:
   - `token` (string): a string to search
   - `maxDistance` (number): maximum Levenshtein / Damerau-Levenshtein distance
   - `transpositions` (bool, _optional_): if set to `false`, a Levenshtein
@@ -465,6 +465,12 @@ Object tokens:
   - `maxTerms` (number, _optional_): consider only a specified number of the
     most relevant terms. One can pass `0` to consider all matched terms, but it may
     impact performance negatively. The default value is `64`.
+  - `prefix` (string, _optional_): if defined, then a search for the exact
+    prefix is carried out, using the matches as candidates. The Levenshtein /
+    Damerau-Levenshtein distance is then computed for each candidate using the
+    remainders of the strings. This option can improve performance in cases where
+    there is a known common prefix. The default value is an empty string
+    (introduced in v3.7.13, v3.8.1).
 - `{STARTS_WITH: [prefix]}`: see [STARTS_WITH()](#starts_with).
   Array brackets are optional
 - `{TERM: [token]}`: equal to `token` but without Analyzer tokenization.
@@ -710,7 +716,7 @@ FOR doc IN viewName
 
 <small>Introduced in: v3.7.0</small>
 
-`LEVENSHTEIN_MATCH(path, target, distance, transpositions, maxTerms) → fulfilled`
+`LEVENSHTEIN_MATCH(path, target, distance, transpositions, maxTerms, prefix) → fulfilled`
 
 Match documents with a [Damerau-Levenshtein distance](https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance){:target=_"blank"}
 lower than or equal to *distance* between the stored attribute value and
@@ -732,6 +738,12 @@ if you want to calculate the edit distance of two strings.
   impact performance negatively. The default value is `64`.
 - returns **fulfilled** (bool): `true` if the calculated distance is less than
   or equal to *distance*, `false` otherwise
+- **prefix** (string, _optional_): if defined, then a search for the exact
+  prefix is carried out, using the matches as candidates. The Levenshtein /
+  Damerau-Levenshtein distance is then computed for each candidate using the
+  remainders of the strings. This option can improve performance in cases where
+  there is a known common prefix. The default value is an empty string
+  (introduced in v3.7.13, v3.8.1).
 
 The Levenshtein distance between _quick_ and _quikc_ is `2` because it requires
 two operations to go from one to the other (remove _k_, insert _k_ at a
@@ -751,6 +763,16 @@ FOR doc IN viewName
   RETURN doc.text
 ```
 
+Match documents with a Levenshtein distance of 1 with the prefix `qui`. The edit
+distance is calculated using the search term `kc` and the stored value without
+the prefix (e.g. `ck`). The prefix `qui` is constant.
+
+```js
+FOR doc IN viewName
+  SEARCH LEVENSHTEIN_MATCH(doc.text, "kc", 1, false, 64, "qui") // matches "quick"
+  RETURN doc.text
+```
+
 You may want to pick the maximum edit distance based on string length.
 If the stored attribute is the string _quick_ and the target string is
 _quicksands_, then the Levenshtein distance is 5, with 50% of the
diff --git a/3.8/aql/functions-arangosearch.md b/3.8/aql/functions-arangosearch.md
index d063d1657e..9055dcdfdc 100644
--- a/3.8/aql/functions-arangosearch.md
+++ b/3.8/aql/functions-arangosearch.md
@@ -457,7 +457,7 @@ Object tokens:
 
 - `{IN_RANGE: [low, high, includeLow, includeHigh]}`:
   see [IN_RANGE()](#in_range). *low* and *high* can only be strings.
-- `{LEVENSHTEIN_MATCH: [token, maxDistance, transpositions, maxTerms]}`:
+- `{LEVENSHTEIN_MATCH: [token, maxDistance, transpositions, maxTerms, prefix]}`:
   - `token` (string): a string to search
   - `maxDistance` (number): maximum Levenshtein / Damerau-Levenshtein distance
   - `transpositions` (bool, _optional_): if set to `false`, a Levenshtein
@@ -465,6 +465,12 @@ Object tokens:
   - `maxTerms` (number, _optional_): consider only a specified number of the
     most relevant terms. One can pass `0` to consider all matched terms, but it may
     impact performance negatively. The default value is `64`.
+  - `prefix` (string, _optional_): if defined, then a search for the exact
+    prefix is carried out, using the matches as candidates. The Levenshtein /
+    Damerau-Levenshtein distance is then computed for each candidate using the
+    remainders of the strings. This option can improve performance in cases where
+    there is a known common prefix. The default value is an empty string
+    (introduced in v3.7.13, v3.8.1).
 - `{STARTS_WITH: [prefix]}`: see [STARTS_WITH()](#starts_with).
   Array brackets are optional
 - `{TERM: [token]}`: equal to `token` but without Analyzer tokenization.
@@ -710,7 +716,7 @@ FOR doc IN viewName
 
 <small>Introduced in: v3.7.0</small>
 
-`LEVENSHTEIN_MATCH(path, target, distance, transpositions, maxTerms) → fulfilled`
+`LEVENSHTEIN_MATCH(path, target, distance, transpositions, maxTerms, prefix) → fulfilled`
 
 Match documents with a [Damerau-Levenshtein distance](https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance){:target=_"blank"}
 lower than or equal to *distance* between the stored attribute value and
@@ -732,6 +738,12 @@ if you want to calculate the edit distance of two strings.
   impact performance negatively. The default value is `64`.
 - returns **fulfilled** (bool): `true` if the calculated distance is less than
   or equal to *distance*, `false` otherwise
+- **prefix** (string, _optional_): if defined, then a search for the exact
+  prefix is carried out, using the matches as candidates. The Levenshtein /
+  Damerau-Levenshtein distance is then computed for each candidate using the
+  remainders of the strings. This option can improve performance in cases where
+  there is a known common prefix. The default value is an empty string
+  (introduced in v3.7.13, v3.8.1).
 
 The Levenshtein distance between _quick_ and _quikc_ is `2` because it requires
 two operations to go from one to the other (remove _k_, insert _k_ at a
@@ -751,6 +763,16 @@ FOR doc IN viewName
   RETURN doc.text
 ```
 
+Match documents with a Levenshtein distance of 1 with the prefix `qui`. The edit
+distance is calculated using the search term `kc` and the stored value without
+the prefix (e.g. `ck`). The prefix `qui` is constant.
+
+```js
+FOR doc IN viewName
+  SEARCH LEVENSHTEIN_MATCH(doc.text, "kc", 1, false, 64, "qui") // matches "quick"
+  RETURN doc.text
+```
+
 You may want to pick the maximum edit distance based on string length.
 If the stored attribute is the string _quick_ and the target string is
 _quicksands_, then the Levenshtein distance is 5, with 50% of the
diff --git a/3.9/aql/functions-arangosearch.md b/3.9/aql/functions-arangosearch.md
index da25124f31..eed071dbfe 100644
--- a/3.9/aql/functions-arangosearch.md
+++ b/3.9/aql/functions-arangosearch.md
@@ -457,7 +457,7 @@ Object tokens:
 
 - `{IN_RANGE: [low, high, includeLow, includeHigh]}`:
   see [IN_RANGE()](#in_range). *low* and *high* can only be strings.
-- `{LEVENSHTEIN_MATCH: [token, maxDistance, transpositions, maxTerms]}`:
+- `{LEVENSHTEIN_MATCH: [token, maxDistance, transpositions, maxTerms, prefix]}`:
   - `token` (string): a string to search
   - `maxDistance` (number): maximum Levenshtein / Damerau-Levenshtein distance
   - `transpositions` (bool, _optional_): if set to `false`, a Levenshtein
@@ -465,6 +465,12 @@ Object tokens:
   - `maxTerms` (number, _optional_): consider only a specified number of the
     most relevant terms. One can pass `0` to consider all matched terms, but it may
     impact performance negatively. The default value is `64`.
+  - `prefix` (string, _optional_): if defined, then a search for the exact
+    prefix is carried out, using the matches as candidates. The Levenshtein /
+    Damerau-Levenshtein distance is then computed for each candidate using the
+    remainders of the strings. This option can improve performance in cases where
+    there is a known common prefix. The default value is an empty string
+    (introduced in v3.7.13, v3.8.1).
 - `{STARTS_WITH: [prefix]}`: see [STARTS_WITH()](#starts_with).
   Array brackets are optional
 - `{TERM: [token]}`: equal to `token` but without Analyzer tokenization.
@@ -710,7 +716,7 @@ FOR doc IN viewName
 
 <small>Introduced in: v3.7.0</small>
 
-`LEVENSHTEIN_MATCH(path, target, distance, transpositions, maxTerms) → fulfilled`
+`LEVENSHTEIN_MATCH(path, target, distance, transpositions, maxTerms, prefix) → fulfilled`
 
 Match documents with a [Damerau-Levenshtein distance](https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance){:target=_"blank"}
 lower than or equal to *distance* between the stored attribute value and
@@ -732,6 +738,12 @@ if you want to calculate the edit distance of two strings.
   impact performance negatively. The default value is `64`.
 - returns **fulfilled** (bool): `true` if the calculated distance is less than
   or equal to *distance*, `false` otherwise
+- **prefix** (string, _optional_): if defined, then a search for the exact
+  prefix is carried out, using the matches as candidates. The Levenshtein /
+  Damerau-Levenshtein distance is then computed for each candidate using the
+  remainders of the strings. This option can improve performance in cases where
+  there is a known common prefix. The default value is an empty string
+  (introduced in v3.7.13, v3.8.1).
 
 The Levenshtein distance between _quick_ and _quikc_ is `2` because it requires
 two operations to go from one to the other (remove _k_, insert _k_ at a
@@ -751,6 +763,16 @@ FOR doc IN viewName
   RETURN doc.text
 ```
 
+Match documents with a Levenshtein distance of 1 with the prefix `qui`. The edit
+distance is calculated using the search term `kc` and the stored value without
+the prefix (e.g. `ck`). The prefix `qui` is constant.
+
+```js
+FOR doc IN viewName
+  SEARCH LEVENSHTEIN_MATCH(doc.text, "kc", 1, false, 64, "qui") // matches "quick"
+  RETURN doc.text
+```
+
 You may want to pick the maximum edit distance based on string length.
 If the stored attribute is the string _quick_ and the target string is
 _quicksands_, then the Levenshtein distance is 5, with 50% of the