Question: Can you recommend a search engine that understands natural language queries and provides contextually relevant results?

If you're looking for a search engine that can handle natural language search queries and return results that are relevant to the context of the query, Exa is a good option. Exa uses embeddings and transformer-based models to process search queries and return high-quality, contextually relevant results as quickly as possible. It can handle natural language queries and is designed to work well with Large Language Models (LLMs) to ensure that authoritative and trustworthy web content is returned. Exa offers a variety of pricing tiers, including a free option, so it can be used for a variety of needs.

Another good option is Algolia, an AI-powered search infrastructure geared for businesses and developers. It marries traditional keyword search with vector understanding and dynamic re-ranking based on user behavior for personalized search results. Algolia supports a variety of use cases, including voice and image search, and offers flexible pricing with a Pay-As-You-Go option and no long-term contracts.

For developers who need a more complete solution, Trieve is a full-stack infrastructure for building search, recommendations and RAG experiences. It offers advanced search capabilities like semantic vector search and private managed embedding models, which makes it a good option for complex search needs. Trieve also offers private data control and flexible hosting options, so you can build a search solution that is secure and customizable.

Last, Meilisearch is an open-source search engine that is geared for fast, relevant results. It supports search-as-you-type and a variety of integrations, including language detection and custom relevance. Meilisearch's API and SDKs are easy to use, and it offers flexible pricing options, so it's a good option for quickly adding search to websites and apps.