diff --git a/spacy/matcher/__init__.py b/spacy/matcher/__init__.py
index a4f164847..2fb347da4 100644
--- a/spacy/matcher/__init__.py
+++ b/spacy/matcher/__init__.py
@@ -1,6 +1,6 @@
-from .matcher import Matcher
+from .matcher import Matcher, _default_fuzzy_compare
 from .phrasematcher import PhraseMatcher
 from .dependencymatcher import DependencyMatcher
 from .levenshtein import levenshtein
 
-__all__ = ["Matcher", "PhraseMatcher", "DependencyMatcher", "levenshtein"]
+__all__ = ["Matcher", "PhraseMatcher", "DependencyMatcher", "levenshtein", "_default_fuzzy_compare"]
diff --git a/spacy/pipeline/entityruler.py b/spacy/pipeline/entityruler.py
index 8154a077d..342f693d5 100644
--- a/spacy/pipeline/entityruler.py
+++ b/spacy/pipeline/entityruler.py
@@ -10,7 +10,7 @@ from ..language import Language
 from ..errors import Errors, Warnings
 from ..util import ensure_path, to_disk, from_disk, SimpleFrozenList, registry
 from ..tokens import Doc, Span
-from ..matcher import Matcher, PhraseMatcher
+from ..matcher import Matcher, PhraseMatcher, _default_fuzzy_compare
 from ..scorer import get_ner_prf
 
 
@@ -86,6 +86,7 @@ class EntityRuler(Pipe):
         ent_id_sep: str = DEFAULT_ENT_ID_SEP,
         patterns: Optional[List[PatternType]] = None,
         scorer: Optional[Callable] = entity_ruler_score,
+        fuzzy_compare: Optional[Callable] = _default_fuzzy_compare
     ) -> None:
         """Initialize the entity ruler. If patterns are supplied here, they
         need to be a list of dictionaries with a `"label"` and `"pattern"`
@@ -117,7 +118,8 @@ class EntityRuler(Pipe):
         self.token_patterns = defaultdict(list)  # type: ignore
         self.phrase_patterns = defaultdict(list)  # type: ignore
         self._validate = validate
-        self.matcher = Matcher(nlp.vocab, validate=validate)
+        self._fuzzy_compare = fuzzy_compare
+        self.matcher = Matcher(nlp.vocab, validate=validate, fuzzy_compare=fuzzy_compare)
         self.phrase_matcher_attr = phrase_matcher_attr
         self.phrase_matcher = PhraseMatcher(
             nlp.vocab, attr=self.phrase_matcher_attr, validate=validate
@@ -337,7 +339,8 @@ class EntityRuler(Pipe):
         self.token_patterns = defaultdict(list)
         self.phrase_patterns = defaultdict(list)
         self._ent_ids = defaultdict(tuple)
-        self.matcher = Matcher(self.nlp.vocab, validate=self._validate)
+        self.matcher = Matcher(self.nlp.vocab, validate=self._validate,
+                               fuzzy_compare=self._fuzzy_compare)
         self.phrase_matcher = PhraseMatcher(
             self.nlp.vocab, attr=self.phrase_matcher_attr, validate=self._validate
         )
diff --git a/spacy/tests/pipeline/test_entity_ruler.py b/spacy/tests/pipeline/test_entity_ruler.py
index 6851e2a7c..5525a10ed 100644
--- a/spacy/tests/pipeline/test_entity_ruler.py
+++ b/spacy/tests/pipeline/test_entity_ruler.py
@@ -382,6 +382,41 @@ def test_entity_ruler_overlapping_spans(nlp, entity_ruler_factory):
     assert doc.ents[0].label_ == "FOOBAR"
 
 
+@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
+def test_entity_ruler_fuzzy_pipe(nlp, entity_ruler_factory):
+    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
+    patterns = [
+        {"label": "HELLO", "pattern": [{"LOWER": {"FUZZY": "hello"}}]}
+    ]
+    ruler.add_patterns(patterns)
+    doc = nlp("helloo")
+    assert len(doc.ents) == 1
+    assert doc.ents[0].label_ == "HELLO"
+
+
+@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
+def test_entity_ruler_fuzzy(nlp, entity_ruler_factory):
+    patterns = [
+        {"label": "HELLO", "pattern": [{"LOWER": {"FUZZY": "hello"}}]}
+    ]
+    ruler = EntityRuler(nlp, patterns=patterns)
+    doc = nlp("helloo")
+    ruler(doc)
+    assert len(doc.ents) == 1
+    assert doc.ents[0].label_ == "HELLO"
+
+
+@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
+def test_entity_ruler_fuzzy_disabled(nlp, entity_ruler_factory):
+    patterns = [
+        {"label": "HELLO", "pattern": [{"LOWER": {"FUZZY": "hello"}}]}
+    ]
+    ruler = EntityRuler(nlp, patterns=patterns, fuzzy_compare=lambda x, y, z: False)
+    doc = nlp("helloo")
+    ruler(doc)
+    assert len(doc.ents) == 0
+
+
 @pytest.mark.parametrize("n_process", [1, 2])
 @pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
 def test_entity_ruler_multiprocessing(nlp, n_process, entity_ruler_factory):