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 | [Pandas-AI](/documentation/frameworks/pandas-ai/)             | Python library to query/visualize your data (CSV, XLSX, PostgreSQL, etc.) in natural language        |
 | [Semantic Router](/documentation/frameworks/semantic-router/) | Python library to build a decision-making layer for AI applications using vector search.             |
 | [Spring AI](/documentation/frameworks/spring-ai/)             | Java AI framework for building with Spring design principles such as portability and modular design. |
+| [Sycamore](/documentation/frameworks/sycamore/)             | Document processing engine for ETL, RAG, LLM-based applications, and analytics on unstructured data. |
 | [txtai](/documentation/frameworks/txtai/)                     | Python library for semantic search, LLM orchestration and language model workflows.                  |
 | [Vanna AI](/documentation/frameworks/vanna-ai/)               | Python RAG framework for SQL generation and querying.                                                |
diff --git a/qdrant-landing/content/documentation/frameworks/sycamore.md b/qdrant-landing/content/documentation/frameworks/sycamore.md
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@@ -0,0 +1,62 @@
+---
+title: Sycamore
+---
+
+## Sycamore
+
+[Sycamore](https://sycamore.readthedocs.io/en/stable/) is an LLM-powered data preparation, processing, and analytics system for complex, unstructured documents like PDFs, HTML, presentations, and more. With Aryn, you can prepare data for GenAI and RAG applications, power high-quality document processing workflows, and run analytics on large document collections with natural language.
+
+You can use the Qdrant connector to write into and read documents from Qdrant collections.
+
+<aside role="status">You can find an end-to-end example usage of the Qdrant connector <a a target="_blank" href="https://github.com/aryn-ai/sycamore/blob/main/examples/simple_qdrant.py">here.</a></aside>
+
+## Writing to Qdrant
+
+To write a Docset to a Qdrant collection in Sycamore, use the `docset.write.qdrant(....)` function. The Qdrant writer accepts the following arguments:
+
+- `client_params`: Parameters that are passed to the Qdrant client constructor. See more information in the [Client API Reference](https://python-client.qdrant.tech/qdrant_client.qdrant_client).
+- `collection_params`: Parameters that are passed into the `qdrant_client.QdrantClient.create_collection` method. See more information in the [Client API Reference](https://python-client.qdrant.tech/_modules/qdrant_client/qdrant_client#QdrantClient.create_collection).
+- `vector_name`: The name of the vector in the Qdrant collection. Defaults to `None`.
+- `execute`: Execute the pipeline and write to Qdrant on adding this operator. If `False`, will return a `DocSet` with this write in the plan. Defaults to `True`.
+- `kwargs`: Keyword arguments to pass to the underlying execution engine.
+
+```python
+ds.write.qdrant(
+    {
+        "url": "http://localhost:6333",
+        "timeout": 50,
+    },
+    {
+        "collection_name": "{collection_name}",
+        "vectors_config": {
+            "size": 384,
+            "distance": "Cosine",
+        },
+    },
+)
+
+```
+
+## Reading from Qdrant
+
+To read a Docset from a Qdrant collection in Sycamore, use the `docset.read.qdrant(....)` function. The Qdrant reader accepts the following arguments:
+
+- `client_params`: Parameters that are passed to the Qdrant client constructor. See more information in the[Client API Reference](https://python-client.qdrant.tech/qdrant_client.qdrant_client).
+- `query_params`: Parameters that are passed into the `qdrant_client.QdrantClient.query_points` method. See more information in the [Client API Reference](https://python-client.qdrant.tech/_modules/qdrant_client/qdrant_client#QdrantClient.query_points).
+- `kwargs`: Keyword arguments to pass to the underlying execution engine.
+
+```python
+docs = ctx.read.qdrant(
+    {
+        "url": "https://xyz-example.eu-central.aws.cloud.qdrant.io:6333",
+        "api_key": "<paste-your-api-key-here>",
+    },
+    {"collection_name": "{collection_name}", "limit": 100, "using": "{optional_vector_name}"},
+).take_all()
+
+```
+
+## 📚 Further Reading
+
+- [Sycamore Reference](https://sycamore.readthedocs.io/en/stable/)
+- [Sycamore](https://github.com/aryn-ai/sycamore/tree/main/examples)