From 490f14977fee6f7a2e5e470f701ab044dab889e5 Mon Sep 17 00:00:00 2001
From: Copple <10214025+kiwicopple@users.noreply.github.com>
Date: Thu, 1 Jun 2023 10:40:21 -0600
Subject: [PATCH] tweaks

---
 apps/www/data/products/vector/pageData.tsx | 4 ++--
 apps/www/pages/vector/Vector.tsx           | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/apps/www/data/products/vector/pageData.tsx b/apps/www/data/products/vector/pageData.tsx
index b4cea2e68a1..13551631bf2 100644
--- a/apps/www/data/products/vector/pageData.tsx
+++ b/apps/www/data/products/vector/pageData.tsx
@@ -12,7 +12,7 @@ export default {
     title: 'Supabase Vector',
     h1: (
       <span key={'vector-h1'} className="heading-gradient">
-        The open source Vector Toolkit  <br />
+        The open source Vector Toolkit <br />
         for Postgres
       </span>
     ),
@@ -20,7 +20,7 @@ export default {
       <>
         Use the Supabase client libraries to store, index, and query your vector embeddings at scale.
         <br className="hidden md:block" />
-        Build AI applications with Postgres and pgvector: the best vector database is the database you already have.
+        Build AI applications with your Postgres and pgvector. The best vector database is the database you already have.
       </>
     ),
     image: '/images/product/vector/vector-hero.svg',
diff --git a/apps/www/pages/vector/Vector.tsx b/apps/www/pages/vector/Vector.tsx
index 68c2b0e25a9..48d8f648014 100644
--- a/apps/www/pages/vector/Vector.tsx
+++ b/apps/www/pages/vector/Vector.tsx
@@ -21,9 +21,9 @@ const EnterpriseCta = dynamic(() => import('~/components/Sections/EnterpriseCta'
 function VectorPage() {
   // base path for images
   const { basePath } = useRouter()
-  const meta_title = 'Supabase Vector | The open source Vector Toolkit for Postgres.'
+  const meta_title = 'Supabase Vector | The open source vector toolkit for Postgres.'
   const meta_description =
-    'An open source toolkit for developing AI applications using Postgres and pgvector. Use the Supabase Vector Toolkit with your favorite ML-models to store, index, and access vector embeddings for any AI use case.'
+    'An open source toolkit for developing AI applications using Postgres and pgvector. Integrate with your favorite ML-models to store, index, and access vector embeddings for any AI use case.'
 
   return (
     <>