Ragie

Ragie is a fully managed RAG-as-a-Service platform for agents and apps needing retrievable context from documents and connected data sources, with Parse and free dev tier.

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Context engine for agentic applications

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.

Core capabilities

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.

Agentic OCR and parsing

Use Ragie Parse to extract tables, forms, charts, key-value pairs, signatures, and other structured elements from messy documents while preserving their document positions.

Managed connectors

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.

Multimodal support

Process text, PDFs, images, audio, and video through one pipeline, including transcription and retrieval for spoken or visual content.

Partitions for isolation

Organize content by tenant, workspace, or customer with partitions to keep retrieval isolated and improve relevance in shared environments.

Advanced retrieval controls

Prioritize relevant or current results with hybrid search, reranking, hierarchical search, entity extraction, and recency bias.

Where Ragie fits

Company knowledge assistants
Build assistants that answer questions from company documents and synced knowledge sources without maintaining a custom retrieval stack.
Document parsing workflows
Extract tables, forms, charts, and key-value pairs from messy documents for downstream workflows that need structured output and traceable source locations.
Tenant-isolated applications
Create multi-tenant SaaS features where each customer or workspace needs isolated retrieval and separate data boundaries.
Context-aware team applications
Support sales or productivity tools that need to surface relevant context from customer notes, internal docs, or connected collaboration systems.
Multimodal search and retrieval
Index audio and video so users can search spoken or visual content and jump to relevant moments with retrieval outputs.

Pros and Cons

Pros

Combines ingestion, indexing, retrieval, and structured extraction in one managed platform.
Supports multiple content types, including PDFs, images, audio, and video.
Provides layout-aware parsing with bounding boxes for traceability.
Offers connectors, MCP access, partitions, and enterprise deployment options for different workflows.
Has a published pricing page with a free developer tier and clear plan structure.

Cons

Pricing is usage-based and plan-dependent, so costs can vary with document volume, audio and video usage, and storage.
The public pages show connector coverage and deployment options, but not a complete integration matrix or detailed setup requirements.

FAQ

How does Ragie fit into an agent or app workflow?

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.

What kinds of content can Ragie process?

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.

What pricing options are available?

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.

Is Ragie only for individual developers?

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.

How is usage billed?

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.

Quick Facts

Category: RAG platform
Primary users: Developers and teams building agents, assistants, and apps
Source domain: ragie.ai
Pricing: Free developer tier; paid plans start at $100/month; enterprise custom pricing
Deployment: Cloud, VPC, or on-prem
Content types: Text, PDFs, images, audio, video