diff --git a/tests/test_raillabel_providerkit/convert/loader_classes/test_loader_understand_ai.py b/tests/test_raillabel_providerkit/convert/loader_classes/test_loader_understand_ai.py
index 0f3859b..97d5585 100644
--- a/tests/test_raillabel_providerkit/convert/loader_classes/test_loader_understand_ai.py
+++ b/tests/test_raillabel_providerkit/convert/loader_classes/test_loader_understand_ai.py
@@ -1,17 +1,13 @@
 # Copyright DB Netz AG and contributors
 # SPDX-License-Identifier: Apache-2.0
 
-import os
-
 import pytest
-import raillabel
-
 
-@pytest.fixture
-def loader():
-    return raillabel.load_.loader_classes.LoaderUnderstandAi()
+from raillabel_providerkit.convert.loader_classes.loader_understand_ai import LoaderUnderstandAi
 
 
+def test_supports_true(json_data):
+    assert LoaderUnderstandAi().supports(json_data["understand_ai_real_life"])
 def test_supports_true(json_data):
     assert LoaderUnderstandAi().supports(json_data["understand_ai_real_life"])
 
@@ -35,95 +31,6 @@ def test_validate_schema__real_life_file__errors(json_data):
     assert len(actual) == 1
     assert "topic" in actual[0]
 
-
-def test_load(json_data):
-    input_data_raillabel = remove_non_parsed_fields(json_data["openlabel_v1_short"])
-    input_data_uai = json_data["understand_ai_t4_short"]
-
-    scene_ground_truth = LoaderRailLabel().load(input_data_raillabel, validate=False)
-    scene = LoaderUnderstandAi().load(input_data_uai, validate=False)
-
-    scene.metadata = scene_ground_truth.metadata
-
-    assert scene.asdict() == scene_ground_truth.asdict()
-
-
-def remove_non_parsed_fields(raillabel_data: dict) -> dict:
-    """Return RailLabel file with frame_data and poly3ds removed."""
-
-    for frame in raillabel_data["openlabel"]["frames"].values():
-
-        if "frame_data" in frame["frame_properties"]:
-            del frame["frame_properties"]["frame_data"]
-
-        for object_id, object in list(frame["objects"].items()):
-            if "poly3d" not in object["object_data"]:
-                continue
-
-            del object["object_data"]["poly3d"]
-            if len(object["object_data"]) == 0:
-                del frame["objects"][object_id]
-
-    return raillabel_data
-
-
-# def test_raillabel_loader_warnings():
-#     scene_dict = {
-#         "metadata": {
-#             "clip_id": "db_3_2021-09-22-14-28-01_2021-09-22-14-44-03",
-#             "external_clip_id": "2021-09-22-14-28-01_2021-09-22-14-44-03",
-#             "project_id": "trains_4",
-#             "export_time": "2023-04-20 01:38 UTC",
-#             "exporter_version": "1.0.0",
-#             "coordinate_system_3d": "FLU",
-#             "coordinate_system_reference": "SENSOR",
-#             "folder_name": "2021-09-22-14-28-01_2021-09-22-14-44-03"
-#         },
-#         "coordinateSystems": [],
-#         "frames": [
-#             {
-#                 "frameId": "000",
-#                 "timestamp": "1632321743.134149",
-#                 "annotations": {
-#                     "2D_BOUNDING_BOX": [
-#                         {
-#                             "id": "78f0ad89-2750-4a30-9d66-44c9da73a714",
-#                             "objectId": "b40ba3ad-0327-46ff-9c28-2506cfd6d934",
-#                             "className": "2D_person",
-#                             "geometry": {
-#                                 "xMin": -1.0,
-#                                 "yMin": -0.5,
-#                                 "xMax": 1,
-#                                 "yMax": 2.5
-#                             },
-#                             "attributes": {},
-#                             "sensor": {
-#                                 "type": "NON_EXISTENT_SENSOR",  # <-- relevant line
-#                                 "uri": "S1206063/rgb_test0.png",
-#                                 "timestamp": "1632321743.100000072"
-#                             }
-#                         }
-#                     ],
-#                     "2D_POLYLINE": [],
-#                     "2D_POLYGON": [],
-#                     "3D_BOUNDING_BOX": [],
-#                     "3D_SEGMENTATION": []
-#                 }
-#             }
-#         ]
-#     }
-#     loader = LoaderUnderstandAi()
-
-#     loader.load(scene_dict, validate=True)
-
-#     assert len(loader.warnings) == 2
-
-#     assert "NON_EXISTENT_SENSOR" in loader.warnings[0]
-#     assert "frame 0" in loader.warnings[0]
-
-#     assert "NON_EXISTENT_SENSOR" in loader.warnings[1]
-#     assert "78f0ad89-2750-4a30-9d66-44c9da73a714" in loader.warnings[1]
-
-# Executes the test if the file is called
+    
 if __name__ == "__main__":
     pytest.main([__file__, "--disable-pytest-warnings", "--cache-clear"])