Ragie AI

Ragie is a fully managed Retrieval-Augmented Generation (RAG) as-a-Service platform designed specifically for developers to build smarter, production-grade AI applications quickly and efficiently. It simplifies the complex process of ingesting, chunking, indexing, and retrieving structured and unstructured data from multiple sources like text files, PDFs, images, audio, and video. Ragie offers seamless integrations with popular data sources such as Google Drive, Notion, and Confluence, along with advanced AI features like entity extraction, summary indexing, and hybrid semantic and keyword search. With enterprise-ready scalability, multi-tenant architecture, and strong security compliance, Ragie accelerates AI application development while ensuring accurate, context-rich, and source-backed responses.

Key Features

• Advanced multimodal data ingestion and indexing (text, PDFs, images, audio, video) with structured chunking and multi-layered retrieval.
• Native connectors and APIs for seamless, secure integration with popular tools like Google Drive and Notion, supporting real-time syncing.
• Built-in AI features including summary indexing, entity extraction, LLM re-ranking, and hybrid semantic-keyword search for high accuracy and reduced hallucinations.
• Enterprise-ready with SOC 2-compliant security, multi-tenant architecture, and scalable infrastructure for any workload size.

Use Cases

• Developers building internal or customer-facing AI chatbots with up-to-date, source-verified knowledge bases.
• Enterprise SaaS products leveraging context-rich retrieval from diverse document types and business data.
• Legal, research, and knowledge management applications requiring fast, reliable access to large volumes of heterogeneous data.