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Introduction

Ragie is a fully managed RAG (Retrieval-Augmented Generation) platform designed to streamline the development and deployment of AI applications. It offers a suite of tools and services to simplify the ingestion, chunking, indexing, and retrieval of data from various sources.

Key Features:

  • Fully Managed RAG Pipeline: Handles parsing, chunking, indexing, and retrieval.
  • Multi-Modal Ingest Pipeline: Processes text, PDFs, images, audio, video, tables, and more.
  • Connectors: Integrates with Google Drive, Confluence, Notion, and other popular data sources.
  • Base Chat: Ready-to-use chat interface for interacting with your knowledge base.
  • SDKs and APIs: Developer-friendly tools for easy integration into existing applications.
  • Enterprise-Grade Security: SOC 2 Type II, GDPR, and HIPAA compliant.

Use Cases:

  • AI Assistants: Powering AI assistants with accurate, company-specific knowledge.
  • Legal Tech: Optimizing legal research with high recall and precision.
  • Sales Tech: Enhancing sales processes with relevant insights from product data and customer interactions.
  • Productivity Tools: Enabling faster decisions and smoother collaboration across teams.

Latest News

Ragie | The Context Engine for Agents , Assistants, and Apps

Ragie | The Context Engine for Agents , Assistants, and Apps

8/4/2026

Or, connect directly to popular data sources like Google Drive and Notion, with built-in OAuth integration. Automatic syncing keeps your data up-to-date, ensuring your application delivers accurate and reliable information. Ragie handles everything—from video and audio to text, images, PDFs, and Pow...

Introducing Ragie, fully managed RAG-as-a-Service

Introducing Ragie, fully managed RAG-as-a-Service

8/4/2026

Ragie solves this by providing a fully managed RAG-as-a-Service platform for developers. Originally developed as a solution for Glue, David Sacks’s new chat application, Ragie implements a robust data ingest pipeline and retrieval API that uses the latest techniques in RAG for chunking, searching, a...

Changelog

Changelog

8/4/2026

Web Crawler (early access) with domain scoping, link-count limits, and depth controls to convert any website into a Ragie-ready corpus. ... Full right-to-left language support (Hebrew, Arabic, Persian, etc.) across ingestion, OCR, indexing, and answer generation so global teams get native-quality re...

Blog: AI, RAG, and App Integration Insights

Blog: AI, RAG, and App Integration Insights

8/4/2026

More news · How We Built Agentic Retrieval at Ragie · Engineering · Oct 20 · Agent Ready Launch Week - Day 5: Enterprise-Grade Security and Compliance · Product Updates · Oct 3 · Agent Ready Launch Week - Day 4: New Connection Options in Ragie Connect ·

Agentic Retrieval

Agentic Retrieval

8/4/2026

Ingests data from various sources like text, PDFs, and images via APIs and direct connectors, ensuring seamless integration and updates. ... Isolates key information from different formats, filtering out irrelevant data. ... Uses techniques like table chunking to break data into meaningful segments ...

Alternatives

  • LlamaIndex

    A data framework for LLM applications, providing tools to build and connect custom data sources for RAG.

  • LangChain

    A popular framework for developing LLM-powered applications, offering extensive modules for building complex RAG pipelines.

  • Pinecone

    A managed vector database service that provides the core indexing and retrieval capabilities essential for RAG systems.

  • Weaviate

    An open-source vector database with built-in RAG capabilities, enabling semantic search and knowledge retrieval.

  • Haystack (deepset)

    An open-source NLP framework designed for building custom search and question-answering systems, including advanced RAG architectures.

  • Cohere RAG

    Offers RAG capabilities as part of its platform, focusing on enterprise-grade search and generation from proprietary data.

  • DataStax Astra DB (RAGStack)

    Provides a managed vector database integrated with a RAG framework, simplifying the deployment of RAG applications.

  • Google Vertex AI Search and Conversation

    A managed service for building generative AI applications, including RAG-powered search and conversational agents.

  • Azure AI Search

    A cloud search service that can be integrated with LLMs to create custom RAG solutions for enterprise data.

  • Vellum

    An LLM operations platform that helps developers build, test, and deploy LLM applications, including robust RAG workflows.

FAQ

User Reviews

4.6/5.0
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Pricing

Pricing Model: Freemium, Subscription, Usage-based

Developer

For personal projects or exploring Ragie

Free

Starter

Perfect for smaller scale projects

$100 / month

Pro

Production ready for small businesses and startups

$500 / month

Enterprise

Dedicated SLAs, designed for growth at scale

Custom pricing

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