Spruce: Scalable Private Outsourced Retrieval Using Compact Embeddings

Spruce is a scalable method for private retrieval of information using compact embeddings, enabling secure outsourced search without exposing queries or data to the server. The technique combines cryptographic protocols with efficient embedding compression, addressing the tension between privacy, computational cost, and retrieval accuracy in enterprise data systems.

Spruce is a scalable method for private retrieval of information using compact embeddings, enabling secure outsourced search without exposing queries or data to the server. The technique combines cryptographic protocols with efficient embedding compression, addressing the tension between privacy, computational cost, and retrieval accuracy in enterprise data systems.

High-quality data pipelines remain the most consistent bottleneck in enterprise AI maturity. QuettaMinds helps clients close the gap between raw data assets and production-ready AI inputs.