Question: I need a tool that can handle semantic vector search and re-ranker models for more accurate search results.

If you need a tool that supports semantic vector search and re-ranker models for better search results, Trieve is a good option. It's a full-stack infrastructure that marries language models with fine-tuning ranking and relevance tools. Trieve supports semantic vector search, SPLADE full-text neural search and hybrid search, so it's good for more sophisticated use cases. It also offers private managed embedding models, and you can deploy it with terraform templates.

Another good option is Pinecone. This vector database is designed for fast query and retrieval, supporting low-latency vector search and metadata filtering. Pinecone integrates with big cloud providers and supports real-time updates and hybrid search. It offers a free starter plan and scalable plans, so it's good for a range of use cases, including enterprise.

Algolia is also a good option. It's AI-powered search infrastructure for building personalized search experiences. Algolia combines keyword search with vector understanding and includes dynamic re-ranking based on user behavior. It's good for a broad range of industries and use cases, including enterprise search and headless commerce.

If you prefer open-source options, Qdrant is a good option. It's designed for fast and scalable vector similarity searches, and Qdrant is designed for cloud-native architecture and high-performance processing of high-dimensional vectors. It integrates with leading embeddings and frameworks and can be deployed in a variety of ways, including a free tier.