How &AI scaled global legal retrieval with Qdrant - Qdrant

What this post added

&AI scaled global legal retrieval by using Qdrant Cloud to manage billions of patent documents. They employed OpenAI's embedding models to transform data into vectors and indexed them in Qdrant. Key technical decisions included using scalar quantization for a balance of retrieval speed and accuracy, and leveraging Qdrant's multi-tenancy feature for data isolation between firms. The architecture focuses on retrieval-first, using Qdrant's payload filtering and HNSW for refined search results.