Cleanup headings, pipelines section

Author: leemthompo

solutions/search/ingest-for-search.md

@@ -21,19 +21,19 @@ Search use cases usually focus on general **content**, typically text-heavy data
 
 Once you've decided how to [deploy Elastic](/deploy-manage/index.md), the next step is getting your content into {{es}}. Your choice of ingestion method depends on where your content lives and how you need to access it.
 
-There are several methods to ingest data into {es} for search use cases. Choose one or more based on your requirements.
+There are several methods to ingest data into {{es}} for search use cases. Choose one or more based on your requirements.
 
 ::::{tip}
 If you just want to do a quick test, you can load [sample data](/manage-data/ingest/sample-data.md) into your {{es}} cluster using the UI.
 ::::
 
-## Ingest data using APIs [es-ingestion-overview-apis] 
+## Use APIs [es-ingestion-overview-apis] 
 
 You can use the [`_bulk` API](https://www.elastic.co/docs/api/doc/elasticsearch/v8/group/endpoint-document) to add data to your {{es}} indices, using any HTTP client, including the [{{es}} client libraries](/solutions/search/site-or-app/clients.md).
 
 While the {{es}} APIs can be used for any data type, Elastic provides specialized tools that optimize ingestion for specific use cases.
 
-## Specialized tools [es-ingestion-overview-general-content]
+## Use specialized tools [es-ingestion-overview-general-content]
 
 You can use these specialized tools to add general content to {{es}} indices.
 
@@ -43,17 +43,8 @@ You can use these specialized tools to add general content to {{es}} indices.
 | [**Search connectors**]() | Third-party integrations to popular content sources like databases, cloud storage, and business applications | Choose from a range of Elastic-built connectors or build your own in Python using the Elastic connector framework|
 | [**File upload**](/manage-data/ingest/tools/upload-data-files.md)| One-off manual uploads through the UI | Useful for testing or very small-scale use cases, but not recommended for production workflows |
 
-### (Optional) Content processing
+### Process data at ingest time
 
-You can also transform and enrich your content at ingest time with ingest pipelines, or at query time with runtime fields. Choose the right approach based on your requirements:
+You can also transform and enrich your content at ingest time using [ingest pipelines](/manage-data/ingest/transform-enrich/ingest-pipelines.md).
 
-| Processing Type | Description | Use cases |
-|----------------|-------------|------------|
-| **Ingest pipelines** | Choose from a range of built-in processors or create custom processors | Data enrichment, content extraction from PDFs, ML inference, custom business logic |
-| **Runtime fields** | Fields computed during query execution | Price calculation with current exchange rates, distance calculations, user-specific scoring |
-
-You can manage ingest pipelines through Elasticsearch APIs or Kibana UIs.
-
-::::{tip}
-The UI also has a set of tools for creating and managing indices optimized for search use cases. You can also manage your ingest pipelines in this UI. Learn more in [](search-pipelines.md)
-::::
+The Elastic UI has a set of tools for creating and managing indices optimized for search use cases. You can also manage your ingest pipelines in this UI. Learn more in [](search-pipelines.md).