diff --git a/vacancies/main/management/commands/collect_vacancies_from_telegram_messages.py b/vacancies/main/management/commands/collect_vacancies_from_telegram_messages.py
index d22d7ce..122018d 100644
--- a/vacancies/main/management/commands/collect_vacancies_from_telegram_messages.py
+++ b/vacancies/main/management/commands/collect_vacancies_from_telegram_messages.py
@@ -1,3 +1,7 @@
+import traceback
+from itertools import batched
+from concurrent.futures import ThreadPoolExecutor
+
 from django.core.management import BaseCommand
 import clickhouse_connect
 from vacancies.main.vector_store import add_vectors, extract_features, qdrant_client
@@ -45,17 +49,24 @@ class Command(BaseCommand):
         exist_points_set = tuple(set(exist_points_ids))
 
         result_rows = clickhouse_client.query(query, parameters={"exist_points": exist_points_set}).result_rows
-        result_rows_len = len(result_rows)
-        for index, row in enumerate(result_rows):
-            (id, chat_username, telegram_id, message, timestamp) = row
+        batch_size = 10
+        with ThreadPoolExecutor(max_workers=batch_size) as pool:
+            pool.map(self._process_batch, batched(result_rows, batch_size))
 
-            link = f"https://t.me/{chat_username}/{telegram_id}"
-            print(f"Processing {index+1}/{result_rows_len} link: {link}")
-            features = extract_features(message)
+    def _process_batch(self, result_rows):
+        try:
+            for index, row in enumerate(result_rows):
+                (id, chat_username, telegram_id, message, timestamp) = row
 
-            add_vectors(
-                "vacancies",
-                id,
-                features.model_dump(),
-                {'content': message, 'features_json': features.model_dump(), "link": link, "timestamp": timestamp},
-            )
+                link = f"https://t.me/{chat_username}/{telegram_id}"
+                print(f"Processing {index+1}/{len(result_rows)} link: {link}")
+                features = extract_features(message)
+
+                add_vectors(
+                    "vacancies",
+                    id,
+                    features.model_dump(),
+                    {'content': message, 'features_json': features.model_dump(), "link": link, "timestamp": timestamp},
+                )
+        except Exception as exc:
+            traceback.print_exception(exc)