diff --git a/litellm/proxy/custom_prompt_management.py b/litellm/proxy/custom_prompt_management.py
new file mode 100644
index 0000000000..7f320ac00a
--- /dev/null
+++ b/litellm/proxy/custom_prompt_management.py
@@ -0,0 +1,36 @@
+from typing import List, Optional, Tuple
+
+from litellm._logging import verbose_logger
+from litellm.integrations.custom_prompt_management import CustomPromptManagement
+from litellm.types.llms.openai import AllMessageValues
+from litellm.types.utils import StandardCallbackDynamicParams
+
+
+class X42PromptManagement(CustomPromptManagement):
+    def get_chat_completion_prompt(
+        self,
+        model: str,
+        messages: List[AllMessageValues],
+        non_default_params: dict,
+        prompt_id: str,
+        prompt_variables: Optional[dict],
+        dynamic_callback_params: StandardCallbackDynamicParams,
+    ) -> Tuple[str, List[AllMessageValues], dict]:
+        """
+        Returns:
+        - model: str - the model to use (can be pulled from prompt management tool)
+        - messages: List[AllMessageValues] - the messages to use (can be pulled from prompt management tool)
+        - non_default_params: dict - update with any optional params (e.g. temperature, max_tokens, etc.) to use (can be pulled from prompt management tool)
+        """
+        verbose_logger.debug(
+            f"in async get chat completion prompt. Prompt ID: {prompt_id}, Prompt Variables: {prompt_variables}, Dynamic Callback Params: {dynamic_callback_params}"
+        )
+
+        return model, messages, non_default_params
+
+    @property
+    def integration_name(self) -> str:
+        return "x42-prompt-management"
+
+
+x42_prompt_management = X42PromptManagement()