diff --git a/src/summary/summary/api/route/tasks.py b/src/summary/summary/api/route/tasks.py
index 42b212bb..0c5bc3b7 100644
--- a/src/summary/summary/api/route/tasks.py
+++ b/src/summary/summary/api/route/tasks.py
@@ -1,10 +1,15 @@
 """API routes related to application tasks."""
 
+from typing import Optional
+
 from celery.result import AsyncResult
 from fastapi import APIRouter
 from pydantic import BaseModel
 
-from summary.core.celery_worker import process_audio_transcribe_summarize
+from summary.core.celery_worker import (
+    process_audio_transcribe_summarize,
+    process_audio_transcribe_summarize_v2,
+)
 
 
 class TaskCreation(BaseModel):
@@ -13,6 +18,7 @@ class TaskCreation(BaseModel):
     filename: str
     email: str
     sub: str
+    version: Optional[int] = 2
 
 
 router = APIRouter(prefix="/tasks")
@@ -21,9 +27,15 @@ router = APIRouter(prefix="/tasks")
 @router.post("/")
 async def create_task(request: TaskCreation):
     """Create a task."""
-    task = process_audio_transcribe_summarize.delay(
-        request.filename, request.email, request.sub
-    )
+    if request.version == 1:
+        task = process_audio_transcribe_summarize.delay(
+            request.filename, request.email, request.sub
+        )
+    else:
+        task = process_audio_transcribe_summarize_v2.delay(
+            request.filename, request.email, request.sub
+        )
+
     return {"id": task.id, "message": "Task created"}
 
 
diff --git a/src/summary/summary/core/celery_worker.py b/src/summary/summary/core/celery_worker.py
index 9ff55578..ad637f4c 100644
--- a/src/summary/summary/core/celery_worker.py
+++ b/src/summary/summary/core/celery_worker.py
@@ -56,6 +56,35 @@ def create_retry_session():
     return session
 
 
+def format_segments(transcription_data):
+    """Format transcription segments from WhisperX into a readable conversation format.
+
+    Processes transcription data with segments containing speaker information and text,
+    combining consecutive segments from the same speaker and formatting them as a
+    conversation with speaker labels.
+    """
+    formatted_output = ""
+    if not transcription_data or not hasattr(transcription_data, 'segments'):
+        if isinstance(transcription_data, dict) and 'segments' in transcription_data:
+            segments = transcription_data['segments']
+        else:
+            return "Error: Invalid transcription data format"
+    else:
+        segments = transcription_data.segments
+
+    previous_speaker = None
+
+    for segment in segments:
+        speaker = segment.get('speaker', 'UNKNOWN_SPEAKER')
+        text = segment.get('text', '')
+        if text:
+            if speaker != previous_speaker:
+                formatted_output += f"\n\n *{speaker}*: {text}"
+            else:
+                formatted_output += f" {text}"
+            previous_speaker = speaker
+    return formatted_output
+
 def post_with_retries(url, data):
     """Send POST request with automatic retries."""
     session = create_retry_session()
@@ -140,3 +169,72 @@ def process_audio_transcribe_summarize(filename: str, email: str, sub: str):
 
     logger.info("Webhook submitted successfully. Status: %s", response.status_code)
     logger.debug("Response body: %s", response.text)
+
+
+@celery.task(max_retries=settings.celery_max_retries)
+def process_audio_transcribe_summarize_v2(filename: str, email: str, sub: str):
+    """Process an audio file by transcribing it and generating a summary.
+
+    This Celery task performs the following operations:
+    1. Retrieves the audio file from MinIO storage
+    2. Transcribes the audio using WhisperX model
+    3. Sends the results via webhook
+
+    """
+    logger.info("Notification received")
+    logger.debug("filename: %s", filename)
+
+    minio_client = Minio(
+        settings.aws_s3_endpoint_url,
+        access_key=settings.aws_s3_access_key_id,
+        secret_key=settings.aws_s3_secret_access_key,
+        secure=settings.aws_s3_secure_access,
+    )
+
+    logger.debug("Connection to the Minio bucket successful")
+
+    audio_file_stream = minio_client.get_object(
+        settings.aws_storage_bucket_name, object_name=filename
+    )
+
+    temp_file_path = save_audio_stream(audio_file_stream)
+    logger.debug("Recording successfully downloaded, filepath: %s", temp_file_path)
+
+    logger.debug("Initiating OpenAI client")
+    openai_client = openai.OpenAI(
+        api_key=settings.openai_api_key, base_url=settings.openai_base_url
+    )
+
+    try:
+        logger.debug("Querying transcription …")
+        with open(temp_file_path, "rb") as audio_file:
+            transcription = openai_client.audio.transcriptions.create(
+                model=settings.openai_asr_model, file=audio_file
+            )
+
+            logger.debug("Transcription: \n %s", transcription)
+    finally:
+        if os.path.exists(temp_file_path):
+            os.remove(temp_file_path)
+            logger.debug("Temporary file removed: %s", temp_file_path)
+
+    formatted_transcription = format_segments(transcription)
+
+    data = {
+        "title": "Transcription",
+        "content": formatted_transcription,
+        "email": email,
+        "sub": sub,
+    }
+
+    logger.debug("Submitting webhook to %s", settings.webhook_url)
+    logger.debug("Request payload: %s", json.dumps(data, indent=2))
+
+    response = post_with_retries(settings.webhook_url, data)
+
+    logger.info("Webhook submitted successfully. Status: %s", response.status_code)
+    logger.debug("Response body: %s", response.text)
+
+    # TODO - integrate summarize the transcript and create a new document.
+
+