Indexing and retrieval
Build vector, keyword, and summary indexes from uploaded content or synced sources, then use Ragie’s retrieval pipeline to surface relevant context for agents and assistants.
RAG como serviço totalmente gerenciado para agentes, assistentes e apps
Ragie is a fully managed RAG-as-a-Service platform for agents, assistants, and applications that need current, retrievable context from documents and other content sources. It combines ingestion, indexing, retrieval, and structured extraction so teams do not have to build and maintain their own retrieval pipeline.
The product supports direct file upload through API and syncs from external systems through connectors. It also processes text, PDFs, images, audio, and video, and includes Parse for layout-aware extraction of structured elements with bounding boxes. For applications that need to isolate data or work across multiple customers, Ragie adds partitions and enterprise deployment options.
Build vector, keyword, and summary indexes from uploaded content or synced sources, then use Ragie’s retrieval pipeline to surface relevant context for agents and assistants.
Use Ragie Parse to extract tables, forms, charts, key-value pairs, signatures, and other structured elements from messy documents while preserving their document positions.
Sync data from Google Drive, Notion, Slack, Confluence, and other connected systems, or embed connectors in your own app so end users can connect their data.
Process text, PDFs, images, audio, and video through one pipeline, including transcription and retrieval for spoken or visual content.
Organize content by tenant, workspace, or customer with partitions to keep retrieval isolated and improve relevance in shared environments.
Prioritize relevant or current results with hybrid search, reranking, hierarchical search, entity extraction, and recency bias.
Build assistants that answer questions from company documents and synced knowledge sources without maintaining a custom retrieval stack.
Extract tables, forms, charts, and key-value pairs from messy documents for downstream workflows that need structured output and traceable source locations.
Create multi-tenant SaaS features where each customer or workspace needs isolated retrieval and separate data boundaries.
Support sales or productivity tools that need to surface relevant context from customer notes, internal docs, or connected collaboration systems.
Index audio and video so users can search spoken or visual content and jump to relevant moments with retrieval outputs.
Ragie ingests content through API uploads or pre-built connectors, then parses, chunks, and indexes it so applications can retrieve context, structured data, or extracted entities through the API.
The source pages show support for documents, PDFs, images, audio, and video, plus the Parse product for layout-aware document extraction. Parse also returns structured elements with bounding boxes for traceability.
The pricing page shows a Developer tier, a Starter plan at $100 per month, a Pro plan at $500 per month, and an Enterprise option with custom pricing and contact sales.
Ragie is designed for teams building context-powered applications, assistants, and workflows. The homepage also highlights options such as partitions, connectors, MCP access, and enterprise deployment paths for larger setups.
The pricing page explains that retrievals, document processing, audio and video usage, and storage are billed differently by plan and usage type. Some plans include included usage and overage pricing, while Enterprise uses custom pricing.
Os dados de tráfego são apenas para referência.
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