Binary quantization reduces the memory footprint of stored vectors by converting floating-point embeddings into compact binary representations. This approach maintains retrieval accuracy while significantly improving storage efficiency, making it suitable for resource-constrained environments and large-scale deployments.

To configure document store to use binary quantization, post a request to the `/api/kb/<storeName>/index` endpoint and specify `BINARY` as the value of the `type` property:

http request
 POST /api/kb/<storeName>/index

 {
    "type": "BINARY",
    "oversamplingFactor": 3
 }

The `oversamplingFactor` property in the payload above can be omitted, as it uses a default value. Its main purpose is to who you how you can override the default.