Bring customer data into your app– right from your app.

Develop faster with Ragie Connect – fully managed connectors for your AI application.

Connectors Data Overview

Embed Ragie connectors directly in your application and let your customers connect and manage their own data.

Connector Hero Image - TableBoost analytics uses Ragie to connect to Dropbox
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Secure access
Fully managed connectors handle authentication and authorization to securely access your customers’ data, no matter where it lives. Automatic syncing keeps data up to date.
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Monitor connections with webhooks
Webhooks provide real-time monitoring by instantly notifying you of connection events or changes, ensuring seamless tracking and faster response to issues.
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Manage your costs with page limits
Take control of your costs by setting page limits per connection, helping you manage usage and accurately predict expenses to fit your business needs.
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White labeling
Deliver a seamless, on-brand experience with fully customizable connectors. Ragie Connect allows you to apply your own branding, ensuring a cohesive look and feel across your application.
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Scaled for enterprise-level demands
Whether you’re working with millions of records or handling peak loads, Ragie Connect is designed for high throughput, bursty workloads, and real-time data processing.
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Developer-friendly pricing
Take control of your costs by setting page limits per connection, helping you manage usage and accurately predict expenses to fit your business needs.
Used in production by
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Every connection is powered by Ragie's advanced RAG engine for best-in-class results

see ragie's advanced rag engine
Parsing
Normalizes inputs across formats like PDFs, DOCs, HTML, and media — creating consistent, structured data ready for processing.
Extraction
Identifies key signals like entities, metadata, and boundaries — laying the groundwork for high-quality, context-aware retrieval.
Chunking
Segments content into logically grouped chunks using type-specific strategies — preserving context and improving recall.
Indexing
Builds vector, keyword, and summary indexes — enabling semantic search, keyword retrieval, and hierarchical high-level recall.
Retrieval
Combines multi-index recall with precision re-ranking — delivering grounded, context-rich results for any LLM.

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