diff --git a/tutorials/how-to-implement-rag-generativeapis/index.mdx b/tutorials/how-to-implement-rag-generativeapis/index.mdx
index bbcd7e9b0d..570689a1fc 100644
--- a/tutorials/how-to-implement-rag-generativeapis/index.mdx
+++ b/tutorials/how-to-implement-rag-generativeapis/index.mdx
@@ -9,7 +9,7 @@ dates:
   validation: 2024-10-10
   posted: 2018-10-10
 categories:
-  - managed-inference
+  - generative-apis
 ---
 
 Retrieval-Augmented Generation (RAG) enhances language models by incorporating relevant information from your own datasets. This hybrid approach improves both the accuracy and contextual relevance of the model's outputs, making it ideal for advanced AI applications.
diff --git a/tutorials/processing-images-structured-outputs-pixtral/index.mdx b/tutorials/processing-images-structured-outputs-pixtral/index.mdx
index 154498886e..f9317e5867 100644
--- a/tutorials/processing-images-structured-outputs-pixtral/index.mdx
+++ b/tutorials/processing-images-structured-outputs-pixtral/index.mdx
@@ -8,6 +8,7 @@ content:
 tags: AI vision-model image-processing Pixtral Mistral structured-data
 categories:
   - managed-inference
+  - generative-apis
 hero: assets/Pixtral-Structured-Outputs.webp
 dates:
   validation: 2024-10-09