Comprehensive 機器學習搜尋 Tools for Every Need

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機器學習搜尋

  • AI-powered search and discovery experiences for the modern world.
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    What is Trieve?
    Trieve offers advanced AI-powered search and discovery solutions, ensuring companies have a competitive edge. Features include semantic vector search, full-text search with BM25 and SPLADE models, and hybrid search capabilities. Trieve also provides relevance tuning, sub-sentence highlighting, and robust API integrations for easy data management. Companies can manage ingestion, embeddings, and analytics effortlessly, leveraging private open-source models for maximum data security. Set up industry-leading search experiences quickly and efficiently.
  • AI_RAG is an open-source framework enabling AI agents to perform retrieval-augmented generation using external knowledge sources.
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    What is AI_RAG?
    AI_RAG delivers a modular retrieval-augmented generation solution that combines document indexing, vector search, embedding generation, and LLM-driven response composition. Users prepare corpora of text documents, connect a vector store like FAISS or Pinecone, configure embedding and LLM endpoints, and run the indexing process. When a query arrives, AI_RAG retrieves the most relevant passages, feeds them alongside the prompt into the chosen language model, and returns a contextually grounded answer. Its extensible design allows custom connectors, multi-model support, and fine-grained control over retrieval and generation parameters, ideal for knowledge bases and advanced conversational agents.
  • Spark Engine is an AI-powered semantic search platform delivering fast, relevant results using vector embeddings and natural language understanding.
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    What is Spark Engine?
    Spark Engine uses advanced AI models to transform text data into high-dimensional vector embeddings, allowing searches to go beyond keyword matching. When a user submits a query, Spark Engine processes it through natural language understanding to capture intent, compares it with indexed document embeddings, and ranks results by semantic similarity. The platform supports filtering, faceting, typo tolerance, and result personalization. With options for customizable relevance weights and analytics dashboards, teams can monitor search performance and refine parameters. Infrastructure is fully managed and horizontally scalable, ensuring low-latency responses under high load. Spark Engine's RESTful API and SDKs for multiple languages make integration straightforward, empowering developers to embed intelligent search into web, mobile, and desktop applications rapidly.
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