diff --git a/README.md b/README.md
index 79e9b40b..da10af32 100644
--- a/README.md
+++ b/README.md
@@ -6,7 +6,7 @@
 **Developer-friendly, serverless vector database for AI applications**
 
 <a href="https://lancedb.github.io/lancedb/">Documentation</a> •
-<a href="https://blog.eto.ai/">Blog</a> •
+<a href="https://blog.lancedb.com/">Blog</a> •
 <a href="https://discord.gg/zMM32dvNtd">Discord</a> •
 <a href="https://twitter.com/lancedb">Twitter</a>
 
@@ -21,15 +21,13 @@ The key features of LanceDB include:
 
 * Production-scale vector search with no servers to manage.
 
-* Optimized for multi-modal data (text, images, videos, point clouds and more).
+* Store, query and filter vectors, metadata and multi-modal data (text, images, videos, point clouds, and more).
 
 * Native Python and Javascript/Typescript support (coming soon).
 
-* Combine attribute-based information with vectors and store them as a single source-of-truth.
-
 * Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure.
 
-* Ecosystem integrations: Apache-Arrow, Pandas, Polars, DuckDB and more on the way.
+* Ecosystem integrations with [LangChain 🦜️🔗](https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/lanecdb.html), [LlamaIndex 🦙](https://gpt-index.readthedocs.io/en/latest/examples/vector_stores/LanceDBIndexDemo.html), Apache-Arrow, Pandas, Polars, DuckDB and more on the way.
 
 LanceDB's core is written in Rust 🦀 and is built using <a href="https://github.com/eto-ai/lance">Lance</a>, an open-source columnar format designed for performant ML workloads.
 
diff --git a/docs/src/index.md b/docs/src/index.md
index 314132cb..2649be27 100644
--- a/docs/src/index.md
+++ b/docs/src/index.md
@@ -6,15 +6,13 @@ The key features of LanceDB include:
 
 * Production-scale vector search with no servers to manage.
 
-* Optimized for multi-modal data (text, images, videos, point clouds and more).
+* Store, query and filter vectors, metadata and multi-modal data (text, images, videos, point clouds, and more).
 
 * Native Python and Javascript/Typescript support (coming soon).
 
-* Combine attribute-based information with vectors and store them as a single source-of-truth.
-
 * Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure.
 
-* Ecosystem integrations: Apache-Arrow, Pandas, Polars, DuckDB and more on the way.
+* Ecosystem integrations with [LangChain 🦜️🔗](https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/lanecdb.html), [LlamaIndex 🦙](https://gpt-index.readthedocs.io/en/latest/examples/vector_stores/LanceDBIndexDemo.html), Apache-Arrow, Pandas, Polars, DuckDB and more on the way.
 
 LanceDB's core is written in Rust 🦀 and is built using Lance, an open-source columnar format designed for performant ML workloads.