Unmanaged Knowledge Banks

An unmanaged Knowledge Bank lets you connect DSS to an existing external vector store that has already been populated. Unlike managed Knowledge Banks (automatically created by DSS when you create a new Embed recipe), DSS does not create or maintain the index content. Instead, DSS uses the existing schema, vectors, and stored text to run retrieval.

Creating an unmanaged Knowledge Bank

To create an unmanaged Knowledge Bank from the Flow:

  • Select + Add Item > Connect or Create

  • Under Knowledge Bank choose an unmanaged vector store type

The following providers are supported for unmanaged Knowledge Banks:

  • Azure AI Search

  • Elasticsearch

  • Pinecone

  • Milvus (remote)

Connection

Use the Connection tab to identify the external index to query.

You must configure the following fields:

  • Connection: Select a DSS connection that already points to the target vector store.

  • Index name: Select the existing index in the target store. (Depending on the vector store provider, this may also be called “Collection” or “Table”.)

  • Embedding model: Select the embedding model that was originally used to generate the vectors stored in the external index.

Important

The embedding model selected in DSS must match the model used to populate the external vector store. If the embeddings were generated with a different model, similarity search results can be significantly degraded or fail completely.

Field mapping

Use the Mapping tab to map fields from the external index schema to the roles expected by DSS. The required fields to configure vary based on the index type and schema.

Metadata fields

You can also control which additional fields from the external index are exposed as metadata in DSS.

These fields can be any metadata columns available in the vector store index.

Refreshing the schema

DSS loads the list of available fields in the Mapping tab from the schema of the external index.

If you change the connection or index, or if the index is externally changed to a different schema, use Refresh Fields to reload the fields before updating the mappings.

Limitations

Unmanaged Knowledge Banks are intended for retrieval on top of an index that already exists outside DSS.

  • The external index schema must already contain the fields needed for retrieval, including the identifier, vector, and content fields.

  • Document-Level Security is not supported for unmanaged Knowledge Banks.

  • All metadata fields are assumed to be filterable. Filtering on a field that is not filterable (e.g., not marked as filterable in Azure AI Search) can lead to unexpected results.

  • Only top-level fields are supported as metadata fields.

For more information about vector store support in DSS, see Working with Vector stores.