diff --git a/examples/vector_databases/neon/README.md b/examples/vector_databases/neon/README.md
index e66b556..132aec1 100644
--- a/examples/vector_databases/neon/README.md
+++ b/examples/vector_databases/neon/README.md
@@ -4,7 +4,7 @@
 
 ## Vector search
 
-Neon supports vector search using the [pgvector](https://neon.tech/docs/extensions/pgvector) open-source PostgreSQL extension, which enable Postgres as a vector database for storing and querying embeddings.
+Neon supports vector search using the [pgvector](https://neon.tech/docs/extensions/pgvector) open-source PostgreSQL extension, which enables Postgres as a vector database for storing and querying embeddings.
 
 ## OpenAI cookbook notebook
 
@@ -17,7 +17,7 @@ In this notebook you will learn how to:
 1. Use embeddings created by OpenAI API
 2. Store embeddings in a Neon Serverless Postgres database
 3. Convert a raw text query to an embedding with OpenAI API
-4. Use Neon with the `pg_vector` extension to perform vector similarity search
+4. Use Neon with the `pgvector` extension to perform vector similarity search
 
 ## Scaling Support