Build Powerful AI-Driven Search and Discovery

Creating relevant search experiences and AI assistants that understand your data is challenging. You're spending months setting up complex machine learning infrastructure, wrestling with embedding models, and struggling to fine-tune relevance. Meanwhile, your users are stuck with basic keyword search that misses their actual intent.

What is Trieve

Trieve is an all-in-one infrastructure API that combines semantic search, recommendations, and RAG (Retrieval Augmented Generation) capabilities without requiring extensive ML knowledge. It empowers developers to build AI-powered search and chatbots with advanced features like date recency biasing, semantic hybrid search, and custom re-ranker models—all through a unified API that can be self-hosted for data privacy or used as a managed service.

Key Capabilities

Semantic Full-Text Hybrid Search : Delivers more accurate results by combining traditional keywords with embedding vectors, capturing both exact matches and contextual meaning for comprehensive discovery.

Date Recency Biasing : Prioritizes newer content in search results, ensuring users see the most timely and relevant information first without overlooking important historical context.

Custom Re-ranker Models : Fine-tunes search relevance without ML expertise, allowing you to adjust ranking algorithms to match specific use cases and improve precision dramatically.

Sub-sentence Highlighting : Pinpoints exact information users need within larger text blocks, reducing time spent scanning documents and improving the overall search experience.

Self-Hosting Option : Maintains complete control over sensitive data with on-premises deployment options, supporting compliance requirements while still leveraging advanced AI capabilities.

Perfect For

A knowledge management team at a growing tech company needed to make their documentation searchable and accessible. With Trieve, they built an intelligent search engine and chatbot in just two weeks that lets employees find exact information across thousands of documents instantly.

An e-commerce developer was struggling with poor product recommendations that hurt conversion rates. After implementing Trieve's recommendation system, customers began discovering relevant products based on browsing history and content similarity, increasing sales by 15%.

Worth Considering

Trieve requires some technical knowledge to implement effectively, making it better suited for developers rather than complete non-technical users. While it offers a generous free tier with 1,000 chunks and basic features, scaling to production use cases requires the usage-based paid plans starting at $25/month plus usage fees. Consider whether your team has the technical resources to maximize its capabilities.

Also Consider

Algolia: Better for teams needing ready-made UI components and simpler implementation with less customization of the underlying search algorithms.

Pinecone: Ideal for vector database needs without the full search feature set, particularly if you're building your own custom ML pipeline.

Weaviate: Consider when working with multimodal search requirements across text, images, and other data types in an open-source environment.

Bottom Line

Trieve stands out by combining search, recommendations, and RAG in a single platform with unmatched control over relevance tuning. If you need to build intelligent search or AI assistants that truly understand your data, Trieve offers the infrastructure to do it faster and with more precision than cobbling together separate tools and services.