Ragie
Managed RAG APIs for indexing multimodal content, retrieving cited context, parsing documents, and extracting entities for agents and applications.
About Ragie
Ragie is a fully managed RAG-as-a-Service platform designed to supply agents, assistants, and applications with usable context. Teams can upload content through an API or sync sources such as Google Drive, Notion, Confluence, and Slack. Ragie then parses, chunks, and indexes text, PDFs, images, audio, and video, building vector, keyword, and summary indexes for hybrid retrieval with citations. Its APIs also cover agentic OCR for tables, forms, charts, and key-value pairs, plain-language entity extraction, reranking, hierarchical search, recency bias, webhooks, and tenant or workspace partitions. A free Developer tier supports evaluation, while Starter and Pro add larger included page volumes and usage-based overages; Enterprise provides custom rates and dedicated SLAs. Prospective users should account for page, media, storage, and extra connector charges. The homepage also states that the Ragie service will end on July 19, so new adopters should confirm current service availability and migration options before integrating it.
Best for
Best use cases
Start with the free tier for a limited proof of concept
Choose Starter or Pro when page-processing allowances match expected volume
Request Enterprise terms when usage, connector branding, or SLA needs require negotiation
Compare before choosing
Managed ingestion and retrieval reduce the infrastructure a team must operate
Multimodal processing and connectors consolidate several content workflows
Usage fees and paid connector add-ons require volume-based cost planning
Features
Build retrieval for AI agents
Index company content and retrieve cited context for agents, assistants, and applications without maintaining a separate retrieval pipeline.
Process multimodal knowledge
Parse, chunk, and index text, PDFs, images, audio, and video through one managed ingestion workflow.
Extract structured document data
Use agentic OCR and entity extraction to capture tables, forms, charts, key-value pairs, and specified entities from documents.
Pros
- Managed ingestion, indexing, and cited retrieval reduce the RAG infrastructure a team has to build and operate.
- One pipeline supports text, PDFs, images, audio, and video, simplifying multimodal knowledge ingestion.
- The free Developer plan offers a bounded way to test retrieval and processing before paying.
Cons
- The homepage says the Ragie service will end on July 19, which creates a critical availability and migration risk for new integrations.
- Starter and Pro can incur page, search, storage, audio, video, and connector charges beyond the monthly subscription.
- Only the first embedded connector is free; every additional connector costs $250 per month.
Pricing Plans
Developer
- Up to 1,000 document and image retrievals
- 1,000 pages of processing included
- 10 GB of audio and video streaming plus 10 processing hours included
Starter
- Unlimited document and image retrievals
- 10,000 pages of processing included
- Additional fast pages at $0.02 per page and hi-res pages at $0.05 per page
- Search and storage at $0.002 per page per month
- Audio at $0.0067 per minute, video at $0.025 per minute, and storage at $0.12 per GB per month
Pro
- Unlimited document and image retrievals
- 60,000 pages of processing included
- The same published overage rates as Starter
- Rerank, hybrid search, hierarchical search, partitions, entity extraction, recency bias, multilingual support, and large-document support
Enterprise
- Unlimited document and image retrievals and page processing
- Custom rates for pages, search, storage, audio, and video
- Whitelabel connectors available as a beta add-on by contacting sales
* Pricing information is for reference only. Please refer to the latest announcement on Ragie's official website.