diff --git a/ui/enriching/image-descriptions.mdx b/ui/enriching/image-descriptions.mdx
index aefa865a..39ceeeab 100644
--- a/ui/enriching/image-descriptions.mdx
+++ b/ui/enriching/image-descriptions.mdx
@@ -2,6 +2,16 @@
 title: Image descriptions
 ---
 
+<iframe
+  width="560"
+  height="315"
+  src="https://www.youtube.com/embed/pMQm9ymM3N8"
+  title="YouTube video player"
+  frameborder="0"
+  allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
+  allowfullscreen
+></iframe>
+
 After partitioning, you can have Unstructured generate text-based summaries of detected images.
 
 This summarization is done by using models offered through various model providers.
diff --git a/ui/enriching/ner.mdx b/ui/enriching/ner.mdx
index e3b65401..7e933224 100644
--- a/ui/enriching/ner.mdx
+++ b/ui/enriching/ner.mdx
@@ -2,6 +2,16 @@
 title: Named entity recognition (NER)
 ---
 
+<iframe
+  width="560"
+  height="315"
+  src="https://www.youtube.com/embed/ZEMegRGjCR0"
+  title="YouTube video player"
+  frameborder="0"
+  allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
+  allowfullscreen
+></iframe>
+
 After partitioning, you can have Unstructured generate a list of recognized entities and their types (such as the names of organizations, products, and people) in the content, through a process known as _named entity recognition_ (NER). 
 You can also have Unstructured generate a list of relationships between the entities that are recognized.
 
diff --git a/ui/enriching/overview.mdx b/ui/enriching/overview.mdx
index 1ae5bca6..c8dc36b2 100644
--- a/ui/enriching/overview.mdx
+++ b/ui/enriching/overview.mdx
@@ -2,6 +2,16 @@
 title: Overview
 ---
 
+<iframe
+  width="560"
+  height="315"
+  src="https://www.youtube.com/embed/brlxpzIpPt0"
+  title="YouTube video player"
+  frameborder="0"
+  allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
+  allowfullscreen
+></iframe>
+
 import EnrichmentImagesTablesHiResOnly from '/snippets/general-shared-text/enrichment-images-tables-hi-res-only.mdx';
 
 _Enriching_ adds enhancments to the processed data that Unstructured produces. These enrichments include:
diff --git a/ui/enriching/table-descriptions.mdx b/ui/enriching/table-descriptions.mdx
index 21b53c48..c8a079dd 100644
--- a/ui/enriching/table-descriptions.mdx
+++ b/ui/enriching/table-descriptions.mdx
@@ -2,6 +2,16 @@
 title: Table descriptions
 ---
 
+<iframe
+  width="560"
+  height="315"
+  src="https://www.youtube.com/embed/3UIW5PDck74"
+  title="YouTube video player"
+  frameborder="0"
+  allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
+  allowfullscreen
+></iframe>
+
 After partitioning, you can have Unstructured generate text-based summaries of detected tables.
 
 This summarization is done by using models offered through various model providers.
diff --git a/ui/enriching/table-to-html.mdx b/ui/enriching/table-to-html.mdx
index e5aff12c..ac7947fa 100644
--- a/ui/enriching/table-to-html.mdx
+++ b/ui/enriching/table-to-html.mdx
@@ -2,6 +2,16 @@
 title: Tables to HTML
 ---
 
+<iframe
+  width="560"
+  height="315"
+  src="https://www.youtube.com/embed/lT2ixyunrvA"
+  title="YouTube video player"
+  frameborder="0"
+  allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
+  allowfullscreen
+></iframe>
+
 After partitioning, you can have Unstructured generate representations of each detected table in HTML markup format.
 
 This table-to-HTML output is done by using [GPT-4o](https://openai.com/index/hello-gpt-4o/), provided through OpenAI.