Trieve

Trieve is an AI search infrastructure platform tailored to deliver more relevant and faster search results.

It combines highly efficient language models with flexible tools for fine-tuning ranking and relevance.

Key features include the ability to conduct semantic and full-text searches that utilize both dense and sparse vectors.

A cross-encoder re-ranker model helps in flame-tuning the search results.

To keep the results relevant to the user, there is a ranking function that allows for biasing based on the recency of the data.

Besides these, Trieve also encompasses features such as document expansion and sub-sentence highlighting.

Users have the freedom to bring in their own embedding model or choose from various open-source models that Trieve hosts.

To further accentuate efficiency, Trieve supports hybrid searches that integrate full-text and semantic vector searches with cross-encoder re-ranker models.

Additionally, it offers private managed embedding models and features like semantic vector search and recency biasing to boost search results.

Trieve also provides solutions for more specific needs like duplicate detection and merging, recommendation based on user's history and content similarity, message history management, and more.

The service is designed to be hosted by the user, offering more control over data privacy and vendor agreements and is made for easy integration with API usage while also offering thorough documentation.

This makes Tieve a powerful, customizable and comprehensive tool for incorporating AI-based search into applications.