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Comprehensive Q&A automatizado Tools for Every Need

Get access to Q&A automatizado solutions that address multiple requirements. One-stop resources for streamlined workflows.

Q&A automatizado

  • OpenKBS

    OpenKBS uses AI-driven embeddings to convert documents into a conversational knowledge base for instant Q&A.
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    What is OpenKBS?
    OpenKBS transforms corporate content—PDFs, docs, web pages—into vector embeddings stored in a knowledge graph. Users interact with an AI chatbot that retrieves precise answers by scanning the semantic index. The platform offers robust API endpoints, customizable UI widgets, and role-based access control. It accelerates internal support, documentation search, and developer onboarding through automated, context-aware responses and continuous learning from new data.
    OpenKBS Core Features
    • Multi-format document ingestion
    • Semantic search with vector embeddings
    • AI chat interface for Q&A
    • REST API for custom integration
    • Role-based access control
    OpenKBS Pro & Cons

    The Cons

    Limited information on specific pricing details on the overview page
    No direct links or apps available on popular mobile or extension stores
    Potential learning curve for new users without prior AI agent development experience

    The Pros

    Cloud platform simplifies AI agent building and deployment
    Provides open-source app blueprints for quick development
    Supports integration with popular platforms like Wordpress
    Accelerates innovation through vibe coding
    OpenKBS Pricing
    Has free planNo
    Free trial details
    Pricing modelPay-as-you-go
    Is credit card requiredNo
    Has lifetime planNo
    Billing frequency
    For the latest prices, please visit: https://openkbs.com/tutorials/overview/

  • rag-services

    rag-services is an open-source microservices framework enabling scalable retrieval-augmented generation pipelines with vector storage, LLM inference, and orchestration.
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    What is rag-services?
    rag-services is an extensible platform that breaks down RAG pipelines into discrete microservices. It offers a document store service, a vector index service, an embedder service, multiple LLM inference services, and an orchestrator service to coordinate workflows. Each component exposes REST APIs, allowing you to mix and match databases and model providers. With Docker and Docker Compose support, you can deploy locally or in Kubernetes clusters. The framework enables scalable, fault-tolerant RAG solutions for chatbots, knowledge bases, and automated document Q&A.
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