---
schema_version: "1"
id: 5998552aea98f2596ff77168dcface3db23313c0d3f9856022000ff04aabdb7d
title: Enriched Indexing of Content Chunks
collection: admin
version: current
locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/data/264-0-0/c360_a_search_index_enriched_index.md
canonical_url: https://help.salesforce.com/s/articleView?id=data.c360_a_search_index_enriched_index.htm&release=264.0.0&type=5
source_site: help.salesforce.com
content_type: documentation
content_hash: 73fe9fc447e0dd80949e2ee5ddb9eae070f0be404bd4834173419df1c6e556ca
description: When you create a vector or hybrid search index from unstructured data in Data 360, you can enrich the generated content chunks by extracting metadata from the content. Extracted metadata includes keywords, entities, topic overviews, questions answered by the content, and content summaries.
products:
  - Data 360
release: "264"
---
# Enriched Indexing of Content Chunks

When you create a vector or hybrid search index from unstructured data in Data 360, you can enrich the generated content chunks by extracting metadata from the content. Extracted metadata includes keywords, entities, topic overviews, questions answered by the content, and content summaries.

Chunk enrichment greatly improves retrieval accuracy, especially in cases in which you can’t use prepend fields (for example, in a UDMO path) and in question and answer agent actions. Enriched content chunks provide an alternative to intensive content curation because LLM-generated content helps improve the identification of the right chunks.

To use enriched content chunks, first create a search index and enable enriched content chunks. In AI Models, create a new custom retriever. When prompted for the search index, select a search index that was created using the enrich chunks option.

To get the most value from an enriched index, access it through a retriever. To use the metadata chunks, a retriever applies extra logic, such as reranking and intent alignment. Calling the index directly through search APIs bypasses the retriever and results in retrieval behavior closer to standard vector or hybrid search. Although introducing a retriever sometimes adds latency, it enables higher retrieval accuracy by improving how queries map to relevant, answer-ready content.

![Note](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-data-data_cloud-264-0-0-production-enus/f3569962-3c9b-4f83-9d0c-b6a574e785da/images/icon_note.png)

Note

Use of this feature in Data Cloud consumes Data 360Credits. For more information see, [Billing Considerations for Unstructured Data and Search Index](https://help.salesforce.com/s/articleView?id=data.c360_a_unstructured_data_billing_considerations.htm&release=264.0.0&type=5 "When you use unstructured data and search index configurations, your data is stored and processed in Data 360. Use of unstructured data and search index in Data 360 impacts the consumption of credits in the following usage types."). Contact your account executive for more information.

## Contents of Enriched Chunks

When you enable enriched content on a vector or hybrid search index, Data 360 generates three chunks: one chunk that contains the original chunk text, one chunk that contains metadata text, and one chunk that contains questions that the chunk can answer. Retrievers access these chunks to use in RAG and AI agent workflows.

![Note](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-data-data_cloud-264-0-0-production-enus/f3569962-3c9b-4f83-9d0c-b6a574e785da/images/icon_note.png)

Note Generated metadata doesn’t include personal identifying information (PII).

<table class="slds-table slds-table_bordered slds-max-medium-table_stacked slds-m-bottom_small ">
        <colgroup>
          <col style="width:33.33333333333333%">
          <col style="width:33.33333333333333%">
          <col style="width:33.33333333333333%">
        </colgroup>
        <thead class="slds-text-title_caps ">
          <tr class="">
            <th scope="col" class="slds-cell-wrap" style="vertical-align:top;" id="d123185e80">Chunk Type</th>
            <th scope="col" class="slds-cell-wrap" style="vertical-align:top;" id="d123185e83">Metadata Type</th>
            <th scope="col" class="slds-cell-wrap" style="vertical-align:top;" id="d123185e86">Description</th>
          </tr>
        </thead>
        <tbody>
          <tr class="">
            <td data-label="Chunk Type" class="slds-cell-wrap" rowspan="5" style="vertical-align:top;" headers="d123185e80 ">METADATA</td>

            <td data-label="Metadata Type" class="slds-cell-wrap" style="vertical-align:top;" headers="d123185e83 ">Keywords</td>

            <td data-label="Description" class="slds-cell-wrap" style="vertical-align:top;" headers="d123185e86 ">
              <p style="margin-bottom:0;">Extracts keywords that uniquely identify the content.</p>
            </td>

          </tr>
          <tr class="">
            <td data-label="Metadata Type" class="slds-cell-wrap" style="vertical-align:top;" headers="d123185e83 ">Entities</td>

            <td data-label="Description" class="slds-cell-wrap" style="vertical-align:top;" headers="d123185e86 ">
              <p>Identifies and lists verbatim any of the following:</p>
              <ul>
                <li>Locations</li>

                <li>Organizations</li>

                <li>Dates</li>

                <li>Time</li>

                <li>Currencies</li>

                <li>Amounts</li>

                <li>Percent</li>

                <li>Products</li>

                <li>Platforms mentioned</li>

              </ul>
            </td>

          </tr>
          <tr class="">
            <td data-label="Metadata Type" class="slds-cell-wrap" style="vertical-align:top;" headers="d123185e83 ">Topics</td>

            <td data-label="Description" class="slds-cell-wrap" style="vertical-align:top;" headers="d123185e86 ">
              <p style="margin-bottom:0;">Extracts main topics discussed in the chunk. Includes important entities and
                keywords in the topic names.</p>
            </td>

          </tr>
          <tr class="">
            <td data-label="Metadata Type" class="slds-cell-wrap" style="vertical-align:top;" headers="d123185e83 ">Title</td>

            <td data-label="Description" class="slds-cell-wrap" style="vertical-align:top;" headers="d123185e86 ">
              <p style="margin-bottom:0;">Generates a concise and informative title summarizing the content.</p>
            </td>

          </tr>
          <tr class="">
            <td data-label="Metadata Type" class="slds-cell-wrap" style="vertical-align:top;" headers="d123185e83 ">Summary</td>

            <td data-label="Description" class="slds-cell-wrap" style="vertical-align:top;" headers="d123185e86 ">Provides a summary of the content, highlighting key topics and entities. If
              possible, aim to encompass a minimum of 100 words and a maximum of 250
              words.</td>

          </tr>
          <tr class="">
            <td data-label="Chunk Type" class="slds-cell-wrap" style="vertical-align:top;" headers="d123185e80 ">QUESTION</td>

            <td data-label="Metadata Type" class="slds-cell-wrap" style="vertical-align:top;" headers="d123185e83 ">Questions</td>

            <td data-label="Description" class="slds-cell-wrap" style="vertical-align:top;" headers="d123185e86 ">If applicable, compiles a comprehensive set of detailed questions that the
              content in the text chunk can answer.</td>

          </tr>
        </tbody>
      </table>

## Data Processing for Enriched Indexing

Enriched indexes are supported in all regions where Data 360 is available. Data for enriched indexes is processed through Amazon Bedrock managed services in these regions.

- us-west-2: US West (Oregon)
- us-east-1: US East (Virginia)
- eu-central-1: Europe (Frankfurt)
- eu-central-2 Europe (Zurich)
- eu-west-3: Europe (Paris)

Enable Amazon Bedrock Models (Amazon and Anthropic) in Einstein Setup to use enriched indexing. For more information, see [Amazon Bedrock documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/batch-inference-supported.html).

- **[Retrieval Response with Enriched Search Index](https://help.salesforce.com/s/articleView?id=data.c360_a_retrieval_response_enriched_index.htm&release=264.0.0&type=5)**  
    Enriched indexing enhances retrieval response by matching a question to a passage with the best possible answer in your knowledge base. While Data 360 hybrid search combines the strengths of sematically aware vector search with the precision and speed of keyword search, enriched indexing closes the gap further by finding the chunks closest to the users' question.

#### See Also

- [Create a Hybrid Search Index with Advanced Setup](https://help.salesforce.com/s/articleView?id=data.c360_a_hybridsearch_index_create.htm&release=264.0.0&type=5 "Configure a hybrid search index for a data model object (DMO) or an unstructured data model object (UDMO) to provide relevant information to generative AI applications. Data 360 breaks up the referenced data into semantically related chunks and generates searchable vectors, and then generates a vector index and a keyword index.")
- [Create a Vector Search Index with Advanced Setup](https://help.salesforce.com/s/articleView?id=data.c360_a_search_index_create_vector_index_config.htm&release=264.0.0&type=5 "When you create a vector search index configuration for a data model object, Data 360 breaks up the referenced data into semantically related chunks and generates searchable vectors. Your RAG and agent workflows use these vectors to find and return semantically similar items when they run queries. To get more granular control over your search index configuration, use the advanced setup, which guides you through each step of the process.")
- [Billing Considerations for Unstructured Data and Search Index](https://help.salesforce.com/s/articleView?id=data.c360_a_unstructured_data_billing_considerations.htm&release=264.0.0&type=5 "When you use unstructured data and search index configurations, your data is stored and processed in Data 360. Use of unstructured data and search index in Data 360 impacts the consumption of credits in the following usage types.")
- [Agentforce Data Library](https://help.salesforce.com/s/articleView?id=ai.data_library_parent.htm&language=en_US)
- [Data Cloud Limits and Guidelines](https://help.salesforce.com/s/articleView?id=data.c360_a_limits_and_guidelines.htm&language=en_US)