diff --git a/haystack/document_stores/deepsetcloud.py b/haystack/document_stores/deepsetcloud.py
index 384929545..83358ce74 100644
--- a/haystack/document_stores/deepsetcloud.py
+++ b/haystack/document_stores/deepsetcloud.py
@@ -46,6 +46,7 @@ class DeepsetCloudDocumentStore(KeywordDocumentStore):
         return_embedding: bool = False,
         label_index: str = "default",
         embedding_dim: int = 768,
+        use_prefiltering: bool = False,
     ):
         """
         A DocumentStore facade enabling you to interact with the documents stored in deepset Cloud.
@@ -86,6 +87,9 @@ class DeepsetCloudDocumentStore(KeywordDocumentStore):
         :param label_index: index for the evaluation set interface
         :param return_embedding: To return document embedding.
         :param embedding_dim: Specifies the dimensionality of the embedding vector (only needed when using a dense retriever, for example, DensePassageRetriever pr EmbeddingRetriever, on top).
+        :param use_prefiltering: By default, DeepsetCloudDocumentStore uses post-filtering when querying with filters.
+                                 To use pre-filtering instead, set this parameter to `True`. Note that pre-filtering
+                                 comes at the cost of higher latency.
         """
         self.index = index
         self.label_index = label_index
@@ -93,6 +97,7 @@ class DeepsetCloudDocumentStore(KeywordDocumentStore):
         self.similarity = similarity
         self.return_embedding = return_embedding
         self.embedding_dim = embedding_dim
+        self.use_prefiltering = use_prefiltering
         self.client = DeepsetCloud.get_index_client(
             api_key=api_key, api_endpoint=api_endpoint, workspace=workspace, index=index
         )
@@ -419,6 +424,7 @@ class DeepsetCloudDocumentStore(KeywordDocumentStore):
             index=index,
             scale_score=scale_score,
             headers=headers,
+            use_prefiltering=self.use_prefiltering,
         )
         docs = [Document.from_dict(doc) for doc in doc_dicts]
         return docs
diff --git a/haystack/utils/deepsetcloud.py b/haystack/utils/deepsetcloud.py
index f62d8908c..bb62471bb 100644
--- a/haystack/utils/deepsetcloud.py
+++ b/haystack/utils/deepsetcloud.py
@@ -379,6 +379,7 @@ class IndexClient:
         all_terms_must_match: Optional[bool] = None,
         scale_score: bool = True,
         headers: Optional[dict] = None,
+        use_prefiltering: Optional[bool] = None,
     ) -> List[dict]:
         index_url = self._build_index_url(workspace=workspace, index=index)
         query_url = f"{index_url}/documents-query"
@@ -391,6 +392,7 @@ class IndexClient:
             "return_embedding": return_embedding,
             "all_terms_must_match": all_terms_must_match,
             "scale_score": scale_score,
+            "use_prefiltering": use_prefiltering,
         }
         response = self.client.post(url=query_url, json=request, headers=headers)
         return response.json()
diff --git a/test/document_stores/test_deepsetcloud.py b/test/document_stores/test_deepsetcloud.py
index 4e5c2995e..d0d33a8c6 100644
--- a/test/document_stores/test_deepsetcloud.py
+++ b/test/document_stores/test_deepsetcloud.py
@@ -379,7 +379,13 @@ class TestDeepsetCloudDocumentStore:
             url=f"{DC_API_ENDPOINT}/workspaces/default/indexes/{DC_TEST_INDEX}/documents-query",
             match=[
                 matchers.json_params_matcher(
-                    {"query_emb": query_emb.tolist(), "top_k": 10, "return_embedding": False, "scale_score": True}
+                    {
+                        "query_emb": query_emb.tolist(),
+                        "top_k": 10,
+                        "return_embedding": False,
+                        "scale_score": True,
+                        "use_prefiltering": False,
+                    }
                 )
             ],
             json=[],