diff --git a/src/classifai/indexers/main.py b/src/classifai/indexers/main.py
index 8c5456c..9637e76 100644
--- a/src/classifai/indexers/main.py
+++ b/src/classifai/indexers/main.py
@@ -67,6 +67,8 @@
     VectorStoreSearchOutput,
 )
 
+_BATCH_SIZE = 128
+
 
 class VectorStore:
     """Models and creates vector databases from CSV text files.
@@ -114,7 +116,7 @@ def __init__(  # noqa: C901, PLR0912, PLR0913, PLR0915
         file_name: str,
         data_type: str,
         vectoriser: VectoriserBase,
-        batch_size: int = 128,
+        batch_size: int = _BATCH_SIZE,
         meta_data: dict | None = None,
         output_dir: str | None = None,
         overwrite: bool = False,
@@ -1062,7 +1064,8 @@ class name must match the vectoriser_class value stored in
                 context={"metadata_path": metadata_in_path, "metadata_type": type(metadata).__name__},
             )
 
-        required_keys = ["vectoriser_class", "vector_shape", "num_vectors", "batch_size", "created_at", "meta_data"]
+        # batch size is not required in metadata for backwards compatibility with v1.0.0
+        required_keys = ["vectoriser_class", "vector_shape", "num_vectors", "created_at", "meta_data"]
         missing = [k for k in required_keys if k not in metadata]
         if missing:
             raise DataValidationError(
@@ -1094,6 +1097,18 @@ class name must match the vectoriser_class value stored in
                 },
             ) from e
 
+        if metadata.get("batch_size") is None:
+            if batch_size is not None:
+                logging.warning(
+                    "Metadata is outdated (pre v1.1.0) and does not contain a batch_size. Using provided batch_size=%d.",
+                    batch_size,
+                )
+            else:
+                logging.warning(
+                    "Metadata is outdated (pre v1.1.0) and does not contain a batch_size. Defaulting to %d.",
+                    _BATCH_SIZE,
+                )
+
         # ---- Load parquet -> IndexBuildError / DataValidationError
         vectors_in_path = os.path.join(folder_path, "vectors.parquet")
         if not in_fs.exists(vectors_in_path):
@@ -1145,7 +1160,7 @@ class name must match the vectoriser_class value stored in
             vector_store.file_name = None
             vector_store.data_type = None
             vector_store.vectoriser = vectoriser
-            vector_store.batch_size = batch_size if batch_size is not None else metadata["batch_size"]
+            vector_store.batch_size = batch_size or metadata.get("batch_size") or _BATCH_SIZE
             vector_store.meta_data = deserialized_column_meta_data
             vector_store.vectors = df
             vector_store.vector_shape = metadata["vector_shape"]