Function & Model Inference

Zilliz Cloud’s Function & Model Inference provides a consistent, configurable way to apply model-based semantic understanding and local mechanisms like BM25 through product-level functions across your search and ranking workflows.

Overview [READ MORE]

Zilliz Cloud provides a unified search architecture for building modern retrieval systems, including semantic search, lexical search, hybrid search, and intelligent reranking. Rather than exposing these capabilities as isolated features, Zilliz Cloud organizes them around a single core abstraction the Function.

BM25 Function [READ MORE]

The BM25 function enables full text search by transforming raw text into sparse vectors and scoring documents based on lexical relevance. It applies term-based matching and frequency-aware weighting to support efficient retrieval of text documents that closely match query terms.

Model-based Functions [READ MORE]

Learn how to use model-based functions in Zilliz Cloud.

Rerank Functions [READ MORE]

Hybrid Search achieves more precise search results through multiple simultaneous ANN searches. Multiple searches return several sets of results, which require a reranking strategy to help merge and reorder the results and return a single set of results. This guide will introduce the reranking strategies supported by Zilliz Cloud and provide tips for selecting the appropriate reranking strategy.

Hosted Models [READ MORE]

Zilliz Cloud can host embedding and reranking models on Zilliz-managed infrastructure. You can deploy dedicated, fully managed model instances and use them directly from Zilliz Cloud for stable and high-performance inference.