What is Trieve AI Search Infrastructure
Trieve AI Search Infrastructure is an all-in-one platform designed to integrate advanced AI search capabilities into applications. It combines state-of-the-art language models with tools for fine-tuning ranking and relevance, making it easier for developers to build robust search, recommendation, and Retrieval-Augmented Generation (RAG) functionalities.
Features of Trieve AI Search Infrastructure
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Private Managed Embedding Models: Users can bring their own embedding models or utilize Trieve's open-source hosted defaults, ensuring data privacy and customization.
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SPLADE Full-Text Neural Search: An advanced retrieval model that outperforms traditional methods like BM25, providing superior full-text search capabilities.
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Semantic Vector Search: Supports semantic search, going beyond keyword matching to understand the context and meaning behind queries.
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Hybrid Search: Combines full-text and semantic vector search with cross-encoder re-ranker models, delivering comprehensive and accurate search results.
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Merchandising Relevance Tuning: Allows boosting search results based on sales or popularity, enhancing user engagement and satisfaction.
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Date Recency Biasing: Prioritizes recent results, ensuring that users get the most up-to-date information.
How to Use Trieve AI Search Infrastructure
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Add Existing Data: Upload your data to the Trieve API, either in chunks or as entire documents that will be processed by Trieve's algorithms.
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Integrate the API: Incorporate API calls into your application's create and update routes to keep your data synchronized.
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Search, Recommend, or Generate: Begin testing search quality using Trieve's management UI, then integrate the search or RAG API calls directly into your product.
Pricing of Trieve AI Search Infrastructure
Trieve offers a flexible pricing model that caters to various needs, from startups to large enterprises. Detailed pricing information can be found on their official website.
Useful Tips for Using Trieve AI Search Infrastructure
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Leverage Hybrid Search: Utilize both full-text and semantic search to enhance the accuracy and relevance of your search results.
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Customize Embedding Models: Tailor your search experience by using or creating custom embedding models that align with your specific data and user needs.
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Monitor and Adjust: Regularly review and adjust your search settings based on user feedback and performance metrics to continually improve the search experience.
Frequently Asked Questions About Trieve AI Search Infrastructure
What types of data can be indexed with Trieve?
Trieve supports a wide range of data types, including text, documents, and more, making it versatile for various applications.
Is Trieve suitable for small businesses?
Yes, Trieve is designed to be scalable and can be used by businesses of all sizes, including small businesses looking to enhance their search capabilities.
How does Trieve ensure data privacy?
Trieve ensures data privacy by allowing users to host their own models and data, with no external dependencies, ensuring that sensitive information remains secure.
Can Trieve be integrated with existing applications?
Absolutely, Trieve is built to be easily integrated with existing applications through its comprehensive API and detailed documentation.
What support does Trieve offer?
Trieve provides extensive support through documentation, a community forum, and direct support channels like email and phone, ensuring that users have the assistance they need.