diff --git a/src/oss/python/integrations/providers/teradata.mdx b/src/oss/python/integrations/providers/teradata.mdx
new file mode 100644
index 0000000000..65333c7151
--- /dev/null
+++ b/src/oss/python/integrations/providers/teradata.mdx
@@ -0,0 +1,30 @@
+---
+title: Teradata
+---
+
+This page covers how to use Teradata Vector Store within LangChain.
+It is broken into two parts: installation and setup, and then references to specific Teradata wrappers.
+
+## Installation
+- Install the Python package with `pip install langchain-teradata`
+
+## Setup
+The first step is to create a connection to your Teradata Vantage system.
+
+    You'll need your Teradata credentials including hostname, username, password, and optionally API tokens for cloud deployments. For detailed setup instructions, see the [Teradata Vector Store User Guide](https://docs.teradata.com/r/Enterprise_IntelliFlex_VMware/Teradata-Vector-Store-User-Guide/Introduction-to-the-Enterprise-Vector-Store-User-Guide)
+and [ Getting started with Vantage Cloud Lake](https://docs.teradata.com/r/Lake-Getting-Started-with-VantageCloud-Lake/)
+
+## Wrappers
+
+### VectorStore
+
+There exists a wrapper around Teradata Vector database, allowing you to use it as a vectorstore, whether for similarity search or rag pipelines
+
+To import this vectorstore:
+```python
+from langchain_teradata import TeradataVectorStore
+```
+
+### Usage
+
+For a more detailed walkthrough of the Teradata VectorStore, refer to [langchain-teradata User Guide](https://docs.teradata.com/r/Enterprise_IntelliFlex_VMware/Teradata-Package-for-LangChain-User-Guide) and [langchain-teradata workflows](https://github.com/Teradata/langchain-teradata)
\ No newline at end of file