Ragie
Ragie is a fully managed RAG-as-a-Service platform that enables developers to build AI applications connected to their own data with outstanding results through advanced features like multimodal processing, context engineering, and seamless integrations.
https://www.ragie.ai/?ref=producthunt
Product Information
Updated:Oct 9, 2025
Ragie Monthly Traffic Trends
Ragie received 36.7k visits last month, demonstrating a Slight Decline of -2.1%. Based on our analysis, this trend aligns with typical market dynamics in the AI tools sector.
View history trafficWhat is Ragie
Ragie is a new AI company founded in 2024 that provides a fully managed Retrieval Augmented Generation (RAG) platform designed specifically for developers. The platform was originally developed as a solution for Glue's chat application and has since evolved into a comprehensive service that helps developers build AI applications by connecting directly to popular data sources like Google Drive, Notion, and Confluence. With $5.5 million in seed funding led by Craft Ventures, Saga VC, Chapter One and Valor, Ragie aims to solve the challenges developers face when building RAG applications by providing a robust data ingest pipeline and retrieval API that implements the latest techniques in RAG for chunking, searching, and re-ranking.
Key Features of Ragie
Ragie is a fully managed RAG-as-a-Service platform that enables developers to build AI applications with advanced data integration capabilities. It offers seamless processing of multiple data types (text, PDFs, audio, video), built-in connectors to popular services like Google Drive and Notion, and advanced features including summary indexing, chunk reranking, and hybrid semantic/keyword search. The platform provides enterprise-grade security, scalable infrastructure, and developer-friendly APIs/SDKs for quick deployment.
Multimodal RAG Processing: Handles diverse content types including text, PDFs, images, audio, and video with automatic transcription and structured parsing for unified retrieval
Advanced Retrieval Engine: Combines multi-index recall with precision re-ranking, using context engineering and LLM-aware optimizations to deliver highly accurate search results
Managed Connectors: Pre-built integrations with popular platforms like Google Drive, Notion, and Confluence, featuring automatic syncing and built-in authentication
Developer-Friendly Tools: Provides comprehensive SDKs, clear APIs, and open-source tools for rapid development and testing of RAG applications
Use Cases of Ragie
Legal Research and Documentation: Enables law firms to quickly search and analyze legal documents with high precision, achieving 99.4% recall accuracy on LegalBench-RAG
E-commerce Intelligence: Helps online retailers analyze product data, customer interactions, and reviews to deliver personalized shopping experiences and insights
Enterprise Knowledge Management: Allows organizations to create intelligent search systems across their internal documents, wikis, and communication channels
Pros
Quick deployment with minimal setup required
Enterprise-grade security with multiple compliance certifications
Comprehensive feature set with advanced RAG capabilities
Strong developer experience with clear documentation and tools
Cons
Some advanced features like SOC2 compliance are still pending/coming soon
Pricing may scale with usage which could be costly for large-scale applications
How to Use Ragie
Get API Key: Sign up at ragie.ai and obtain your Ragie API key from the dashboard
Install SDK: Install Ragie client using npm (for TypeScript) or pip (for Python). Example: 'npm i ragie' or 'pip install ragie'
Initialize Client: Create a new Ragie client instance using your API key. Example: const ragie = new Ragie({ auth: process.env.RAGIE_API_KEY })
Upload Documents: Use the documents.create or documents.createRaw method to upload your data. Ragie supports various file types including text, PDFs, images, audio and video
Wait for Processing: Check document status using documents.get method and wait until status is 'ready', indicating processing is complete
Retrieve Information: Use the retrievals.retrieve method with your query to get relevant chunks of information from your uploaded documents
Optional: Add Connectors: For data from services like Google Drive, Notion, etc., use Ragie Connect to set up connectors and sync data automatically
Optional: Configure Partitions: Use partitions to logically separate data for multi-tenancy and focused retrieval if needed
Optional: Set Up Webhooks: Configure webhooks to monitor events and track document processing status in real-time
Integrate with LLM: Use the retrieved chunks as context in your LLM prompts to generate accurate, data-grounded responses
Ragie FAQs
Ragie is a fully managed RAG-as-a-Service platform designed for developers to streamline the ingestion, chunking, and multimodal indexing of structured and unstructured data. It provides secure retrieval augmented generation APIs with simple SDKs and integrations for building AI applications.
Ragie Video
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Analytics of Ragie Website
Ragie Traffic & Rankings
36.7K
Monthly Visits
#506474
Global Rank
#1823
Category Rank
Traffic Trends: Jul 2024-Jun 2025
Ragie User Insights
00:02:32
Avg. Visit Duration
5.73
Pages Per Visit
43.16%
User Bounce Rate
Top Regions of Ragie
US: 40.98%
IN: 20.44%
GB: 19.36%
CA: 3.62%
NL: 2.54%
Others: 13.06%
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