diff --git a/scripts/run_pipeline.py b/scripts/run_pipeline.py
index 29d3199..eb588d6 100644
--- a/scripts/run_pipeline.py
+++ b/scripts/run_pipeline.py
@@ -4,12 +4,16 @@ import os
 from glob import glob
 from operator import truth
 
-from image_prediction.pipeline import load_pipeline
+from image_prediction.config import CONFIG
+from image_prediction.locations import MLRUNS_DIR
+from image_prediction.pipeline import load_model, load_pipeline
 from image_prediction.utils import get_logger
 from image_prediction.utils.pdf_annotation import annotate_pdf
 
 logger = get_logger()
 
+MODEL = load_model(MLRUNS_DIR, CONFIG)
+
 
 def parse_args():
     parser = argparse.ArgumentParser()
@@ -34,14 +38,16 @@ def process_pdf(pipeline, pdf_path, metadata=None, page_range=None):
         predictions = list(pipeline(f.read(), page_range=page_range, metadata_per_image=metadata))
 
     annotate_pdf(
-        pdf_path, predictions, os.path.join("/tmp", os.path.basename(pdf_path.replace(".pdf", f"_{truth(metadata)}_annotated.pdf")))
+        pdf_path,
+        predictions,
+        os.path.join("/tmp", os.path.basename(pdf_path.replace(".pdf", f"_{truth(metadata)}_annotated.pdf"))),
     )
 
     return predictions
 
 
 def main(args):
-    pipeline = load_pipeline(verbose=True, tolerance=3)
+    pipeline = load_pipeline(model=MODEL, verbose=True, tolerance=3)
 
     if os.path.isfile(args.input):
         pdf_paths = [args.input]
diff --git a/src/serve.py b/src/serve.py
index ece6a0b..de94f03 100644
--- a/src/serve.py
+++ b/src/serve.py
@@ -3,17 +3,21 @@ import io
 import json
 import logging
 
-from image_prediction.config import Config
-from image_prediction.locations import CONFIG_FILE
-from image_prediction.pipeline import load_pipeline
-from image_prediction.utils.banner import load_banner
-from image_prediction.utils.process_wrapping import wrap_in_process
 from pyinfra import config
 from pyinfra.queue.queue_manager import QueueManager
 from pyinfra.storage.storage import get_storage
 
+from image_prediction.config import CONFIG, Config
+from image_prediction.locations import CONFIG_FILE, MLRUNS_DIR
+from image_prediction.pipeline import load_model, load_pipeline
+from image_prediction.utils.banner import load_banner
+from image_prediction.utils.process_wrapping import wrap_in_process
+
 PYINFRA_CONFIG = config.get_config()
 IMAGE_CONFIG = Config(CONFIG_FILE)
+MODEL = load_model(MLRUNS_DIR, CONFIG)
+BUCKET = PYINFRA_CONFIG.storage_bucket
+STORAGE = get_storage(PYINFRA_CONFIG)
 
 logging.getLogger().addHandler(logging.StreamHandler())
 logger = logging.getLogger("main")
@@ -26,17 +30,14 @@ logger.setLevel(PYINFRA_CONFIG.logging_level_root)
 # FIXME: Find more fine-grained solution or if the problem occurs persistently for python services,
 # FIXME: move the process wrapper to a general module (see RED-4929).
 @wrap_in_process
-def process_request(request_message):
+def process_request(request_message, bucket=BUCKET, storage=STORAGE, model=MODEL, img_config=IMAGE_CONFIG):
     dossier_id = request_message["dossierId"]
     file_id = request_message["fileId"]
     target_file_name = f"{dossier_id}/{file_id}.{request_message['targetFileExtension']}"
     response_file_name = f"{dossier_id}/{file_id}.{request_message['responseFileExtension']}"
     figure_data_file_name = f"{dossier_id}/{file_id}.FIGURE.json.gz"
 
-    bucket = PYINFRA_CONFIG.storage_bucket
-    storage = get_storage(PYINFRA_CONFIG)
-
-    pipeline = load_pipeline(verbose=IMAGE_CONFIG.service.verbose, batch_size=IMAGE_CONFIG.service.batch_size)
+    pipeline = load_pipeline(model=model, verbose=img_config.service.verbose, batch_size=img_config.service.batch_size)
 
     if storage.exists(bucket, target_file_name):
         should_publish_result = True