diff --git a/docs/components/vectordbs/dbs/azure_ai_search.mdx b/docs/components/vectordbs/dbs/azure_ai_search.mdx
index 4243cc3f..a764f3c2 100644
--- a/docs/components/vectordbs/dbs/azure_ai_search.mdx
+++ b/docs/components/vectordbs/dbs/azure_ai_search.mdx
@@ -1,5 +1,3 @@
-# Azure AI Search
-
 [Azure AI Search](https://learn.microsoft.com/azure/search/search-what-is-azure-search/) (formerly known as "Azure Cognitive Search") provides secure information retrieval at scale over user-owned content in traditional and generative AI search applications.
 
 ## Usage
diff --git a/docs/components/vectordbs/dbs/pinecone.mdx b/docs/components/vectordbs/dbs/pinecone.mdx
index 31afb64b..8eeb625f 100644
--- a/docs/components/vectordbs/dbs/pinecone.mdx
+++ b/docs/components/vectordbs/dbs/pinecone.mdx
@@ -1,5 +1,3 @@
-# Pinecone
-
 [Pinecone](https://www.pinecone.io/) is a fully managed vector database designed for machine learning applications, offering high performance vector search with low latency at scale. It's particularly well-suited for semantic search, recommendation systems, and other AI-powered applications.
 
 > **Note**: Before configuring Pinecone, you need to select an embedding model (e.g., OpenAI, Cohere, or custom models) and ensure the `embedding_model_dims` in your config matches your chosen model's dimensions. For example, OpenAI's text-embedding-ada-002 uses 1536 dimensions.