diff --git a/docs/assets/images/guides/python/environment_overview.png b/docs/assets/images/guides/python/environment_overview.png
index 0b0e4ad60..56d51c148 100644
Binary files a/docs/assets/images/guides/python/environment_overview.png and b/docs/assets/images/guides/python/environment_overview.png differ
diff --git a/docs/user_guides/projects/python/python_env_overview.md b/docs/user_guides/projects/python/python_env_overview.md
index 1f337a91e..63a0d5c9b 100644
--- a/docs/user_guides/projects/python/python_env_overview.md
+++ b/docs/user_guides/projects/python/python_env_overview.md
@@ -53,6 +53,7 @@ The `MODEL INFERENCE` environments can be used in a deployment using a custom pr
 * `tensorflow-inference-pipeline` to load and serve TensorFlow models
 * `torch-inference-pipeline` to load and serve PyTorch models
 * `pandas-inference-pipeline` to load and serve XGBoost, Catboost and Sklearn models
+* `vllm-inference-pipeline` to load and serve LLMs with vLLM inference engine
 * `minimal-inference-pipeline` to install your own custom framework, contains a minimal set of dependencies
 
 ## Next steps