Trieve
4.75
0
Trieve is an AI platform for fast, relevant searches, supporting semantic and full-text queries with advanced ranking tools.
What is Trieve?
Trieve is an AI search infrastructure platform designed to deliver relevant and fast search results by combining efficient language models with tools for fine-tuning ranking and relevance. It supports semantic and full-text searches using dense and sparse vectors, along with features like a cross-encoder re-ranker model for refining search results. Trieve allows the integration of open-source or custom embedding models and offers hybrid search functionalities that combine full-text and semantic vector searches with cross-encoder re-ranker models. Users can benefit from private managed embedding models, semantic vector search, recency biasing, and other features to enhance search results. Additionally, Trieve provides solutions for specific needs such as duplicate detection, content similarity-based recommendation, and more. It is self-hostable, giving users control over data privacy with easy API integration and thorough documentation, making it a powerful tool for incorporating AI-based search into applications.
Who created Trieve?
Trieve was created by DevFlow Inc. It was launched on March 11, 2024, and is a comprehensive AI search infrastructure platform designed to deliver fast and relevant search results. The platform offers features such as semantic and full-text searches, hybrid search capabilities, private open-source models, and tools for fine-tuning ranking and relevance. Users can bring their own embedding models or utilize the ones provided by Trieve. The platform also supports AI-native end-to-end API and self-hosting options for maximum control over data privacy and usage. Overall, Trieve is a powerful and customizable tool for implementing AI-based search functionalities into applications.
What is Trieve used for?
- Choose between state-of-the-art retrieval models for full-text search
- Support hybrid search combining full-text and semantic vector search
- Tune and boost search results through merchandising and relevance tuning
- Enable sub-sentence highlighting in search results
- Manage ingestion, embeddings, and analytics with ease
- Build unfair competitive advantages through search, discovery, and RAG experiences
- Utilize private open-source models and LLMs running on Trieve servers
- Cover various functions including chunking, ingestion, search, recommendations, RAG, and front-end
- Self-host Trieve for maximum performance and data privacy
- Set up industry-leading search in 30 minutes
Who is Trieve for?
- Developers
- Researchers
- Data scientists
- Content creators
How to use Trieve?
To use Trieve, follow these steps:
- Add Existing Data: Upload individual chunks or entire documents via the API or the no-code dashboard; the data will be chunked by Trieve's algorithms.
- Integrate the API: Add calls to the Trieve API on your create and update routes to keep your data current.
- Search, Recommend, or Generate: Test and fine-tune search, recommendations, and chat quality using the search playground; then, integrate the API calls into your product.
Trieve is an all-in-one infrastructure for creating search, discovery, and RAG experiences, offering semantic vector search, full-text search, hybrid search, customizable embedding models, and more. It emphasizes transparency, data portability, and easy communication with the developers. Trieve is self-hostable, allowing users to maximize data privacy and performance. It provides comprehensive tools for tuning search quality and relevance, making it a versatile and powerful tool for incorporating AI-driven search into applications.
For more information, visit Trieve on GitHub at devflowinc/trieve.
Trieve Pricing and plans
Paid plans start at $2999/Month and include:
- Up to 99.99% uptime SLA
- Up to 125ms P95 hybrid search SLO
- 1000 requests per second
- 1 hour maximum response time
- Load your own custom models for embeddings, LLMs, and reranking
- VPC peering
Trieve FAQs
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What is Trieve?
- Trieve is an AI search infrastructure platform tailored to deliver more relevant and faster search results.
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What are some key features of Trieve?
- Trieve offers semantic and full-text searches utilizing both dense and sparse vectors, cross-encoder re-ranker models, ranking biasing based on data recency, document expansion, and sub-sentence highlighting.
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Can users bring their own embedding model to Trieve?
- Yes, users have the freedom to bring in their own embedding model or choose from various open-source models hosted by Trieve.
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Does Trieve support hybrid searches?
- Yes, Trieve supports hybrid searches that integrate full-text and semantic vector searches with cross-encoder re-ranker models.
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What solutions does Trieve provide for specific needs?
- Trieve provides solutions for duplicate detection and merging, recommendation based on user's history and content similarity, message history management, and more.
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Is Trieve self-hostable?
- Yes, Trieve is designed to be hosted by the user, offering more control over data privacy and vendor agreements.
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How can companies benefit from using Trieve?
- Trieve helps companies build unfair competitive advantages through their search, discovery, and RAG experiences by delivering highly relevant and fast search results.
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Where can Trieve be found?
- Trieve can be found on Github at devflowinc/trieve.
Get started with Trieve
Trieve reviews
Kiran Sharma
March 1, 2025
What do you like most about using Trieve?
The speed and relevance of search results are outstanding. Trieve's ability to handle semantic and full-text queries simultaneously is a game-changer for our applications.
What do you dislike most about using Trieve?
The initial setup can be a bit complex for users who are not technically inclined, but the documentation helps a lot.
What problems does Trieve help you solve, and how does this benefit you?
Trieve has significantly improved our search capabilities, allowing us to find relevant content quickly. This has enhanced user satisfaction and reduced time spent on searches.
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Yuki Tanaka
January 11, 2025
What do you like most about using Trieve?
I love the hybrid search functionality. Being able to combine both full-text and semantic searches allows us to tailor our queries for better precision.
What do you dislike most about using Trieve?
It would be helpful to have more examples in the documentation, particularly for advanced features like custom embeddings.
What problems does Trieve help you solve, and how does this benefit you?
Trieve helps us improve our content recommendation system by offering more accurate suggestions based on content similarity, leading to higher engagement.
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Amir Khan
March 4, 2025
What do you like most about using Trieve?
The performance of the cross-encoder re-ranker model is impressive. It fine-tunes search results effectively, increasing the relevance of our outputs.
What do you dislike most about using Trieve?
There are occasional lags during heavy traffic, but overall performance is still commendable.
What problems does Trieve help you solve, and how does this benefit you?
Trieve has enabled us to detect duplicate content effectively, which has streamlined our content management process and improved our SEO rankings.
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