Ragie

Ragie is a fully managed RAG-as-a-Service platform designed for developers to connect their applications to their users' data and power advanced retrieval-augmented generation (RAG) workflows. It provides pre-built connectors, easy APIs/SDKs, automatic data syncing, and a suite of AI-oriented features to accelerate building contextual, up-to-date AI applications without the overhead of building and maintaining a RAG pipeline from scratch.

Key capabilities include seamless ingestion, chunking, embedding into vectors, and multimodal indexing for structured and unstructured data from sources like Google Drive, Notion, Confluence, and more. Ragie emphasizes data security, privacy, scalability, and a developer-friendly experience with performance-rich features such as LLM re-ranking, summary indexing, entity extraction, and hybrid semantic/keyword search.

How Ragie Works

1. Ingest: Upload data or connect to sources via simple APIs or direct connectors. Supported content includes text docs, PDFs, images, and presentations. Automatic syncing keeps data current.
2. Chunk & Index: Ragie chunks the data and embeds it into vectors using multilingual LLMs. It builds vector, summary, and keyword indexes and stores them in a scalable vector store.
3. Retrieve: Use Ragie’s retrieval API to fetch the most relevant content for a query. Advanced features refine results for accuracy and relevance.

Ragie’s workflow is designed to cut development time, reduce complexity, and deliver up-to-date, context-rich AI responses.

Core Features

• Fully managed RAG service for developers
• Pre-built connectors to data sources (Google Drive, Notion, Confluence, and more)
• Automatic data syncing to keep information current
• Simple APIs and SDKs for quick integration
• Multimodal data processing (text, PDFs, images, presentations)
• Automatic chunking and vectorization using multilingual LLMs
• Out-of-the-box vector, summary, and keyword indexing
• Advanced retrieval capabilities with LLM re-ranking
• Hybrid semantic and keyword search for higher precision
• Hierarchical and partitioned search for scalable, multi-tenant scenarios
• Entity extraction and recency bias to surface structured data (emails, dates, etc.)
• Security-focused: AES-256 encryption at rest, TLS in transit, and certifications (CASA, GDPR, CCPA)
• Transparent pricing with a free tier and scalable plans

Use Cases

• Internal chatbots and virtual assistants that answer from your own data
• Enterprise knowledge bases with accurate, up-to-date responses
• AI-powered document search and summarization for legal, HR, and compliance
• Contextual recommendations and decision support in SaaS apps

Security and Compliance

• Data ownership remains with you; Ragie does not use your data for training
• Encryption at rest (AES-256) and in transit (TLS)
• Compliance certifications including CASA, GDPR, CCPA; SOC2 Type II coming soon

Pricing

• Transparent pricing with a free tier for experimentation, plus Starter, Pro, and Enterprise plans
• No hidden setup fees or surprises; designed to align with modern app development and deployment workflows