diff --git a/cognee/api/v1/cognify/cognify.py b/cognee/api/v1/cognify/cognify.py
index 21d750875..aaf2939ba 100644
--- a/cognee/api/v1/cognify/cognify.py
+++ b/cognee/api/v1/cognify/cognify.py
@@ -22,6 +22,7 @@ from cognee.tasks.graph import extract_graph_from_data
 from cognee.tasks.storage import add_data_points
 from cognee.tasks.summarization import summarize_text
 from cognee.modules.pipelines.layers.pipeline_execution_mode import get_pipeline_executor
+from cognee.tasks.temporal_graph import extract_events_and_entities
 
 logger = get_logger("cognify")
 
@@ -39,6 +40,7 @@ async def cognify(
     graph_db_config: dict = None,
     run_in_background: bool = False,
     incremental_loading: bool = True,
+    temporal_cognify: bool = False,
 ):
     """
     Transform ingested data into a structured knowledge graph.
@@ -177,7 +179,10 @@ async def cognify(
         - LLM_RATE_LIMIT_ENABLED: Enable rate limiting (default: False)
         - LLM_RATE_LIMIT_REQUESTS: Max requests per interval (default: 60)
     """
-    tasks = await get_default_tasks(user, graph_model, chunker, chunk_size, ontology_file_path)
+    if temporal_cognify:
+        tasks = await get_temporal_tasks(user, graph_model, chunker, chunk_size, ontology_file_path)
+    else:
+        tasks = await get_default_tasks(user, graph_model, chunker, chunk_size, ontology_file_path)
 
     # By calling get pipeline executor we get a function that will have the run_pipeline run in the background or a function that we will need to wait for
     pipeline_executor_func = get_pipeline_executor(run_in_background=run_in_background)
@@ -224,3 +229,20 @@ async def get_default_tasks(  # TODO: Find out a better way to do this (Boris's
     ]
 
     return default_tasks
+
+async def get_temporal_tasks(
+    user: User = None, chunker=TextChunker, chunk_size: int = None
+) -> list[Task]:
+    temporal_tasks = [
+        Task(classify_documents),
+        Task(check_permissions_on_dataset, user=user, permissions=["write"]),
+        Task(
+            extract_chunks_from_documents,
+            max_chunk_size=chunk_size or get_max_chunk_tokens(),
+            chunker=chunker,
+        ),
+        Task(extract_events_and_entities, task_config={"chunk_size": 10}),
+        Task(add_data_points, task_config={"batch_size": 10}),
+    ]
+
+    return temporal_tasks