Ragie

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 offers simple APIs and SDKs, seamless integration with sources like Google Drive, Notion, and Confluence, and built-in capabilities like summary indexing, chunk reranking, flexible vector filtering, and hybrid semantic-keyword search. With agentic retrieval for multi-step reasoning and a context-aware MCP Server that enables intelligent tool use, Ragie helps applications deliver state-of-the-art, agent-ready generative AI.

Key Features

• Connects AI applications to data via simple APIs or direct data source connections with built-in OAuth.
• Automatically chunks and embeds data into vectors using multilingual LLMs.
• Builds vector, summary, and keyword indexes to organize information.
• Retrieval API with LLM re-ranking, summary index, entity extraction, and hybrid semantic-keyword search.
• Supports video, audio, text, images, PDFs, and PowerPoint presentations.
• SOC 2 Type II, GDPR, and HIPAA compliant with AES-256 encryption at rest and TLS in transit.

Who It’s For

Ideal for developers building AI applications that leverage their own data for accurate and relevant outputs, from startups to enterprises wanting to avoid the complexities of setting up a RAG pipeline.

Key Benefits

• Fully managed RAG-as-a-Service reduces setup complexity
• Simple APIs and SDKs for quick integration
• Built-in advanced features like summary index, entity extraction, and hybrid search
• SOC 2 Type II, GDPR, and HIPAA compliant