llms.txt Content
# Ragie
> Ragie is a fully managed RAG-as-a-Service platform for developers - covering ingestion, extraction, chunking, multi-index (vector/keyword/summary) indexing, and high-precision retrieval, with SDKs and APIs for rapid production use.
Important notes:
- Built for production: multi-tenant architecture; enterprise features; does not use your data for training.
- Core pipeline stages are: parsing -> extraction -> refinement -> chunking -> indexing -> retrieval.
- Best entry points for developers are the "Getting Started" guide and the API reference.
## Docs (start here)
- [Getting Started](https://docs.ragie.ai/docs/getting-started): Overview, quick setup, key concepts.
- [API Reference](https://docs.ragie.ai/reference): REST endpoints including Documents, Retrievals, Connectors, Partitions, Entities, Webhooks.
- [Tools & SDKs](https://docs.ragie.ai/docs/tools-and-sdks): Python & TypeScript clients and helpers.
- [Connectors](https://docs.ragie.ai/docs/connectors/overview): Native integrations (e.g., Google Drive, Confluence, Notion, Slack, etc.).
- [Webhooks](https://docs.ragie.ai/docs/advanced-features/webhooks): Event flow for monitoring & orchestration.
- [Rate Limits & Errors](https://docs.ragie.ai/docs/troubleshooting/rate-limits): Operational guidance for robust integrations.
## Quick API landings
- [Create Document](https://docs.ragie.ai/reference/createdocument): Ingest; statuses progress through `pending -> ... -> ready`.
- [Retrieve](https://docs.ragie.ai/reference/retrieve): Semantic retrieval with options like rerank and metadata filtering.
- [Connections API](https://docs.ragie.ai/reference/list-connections): Manage connectors and trigger sync.
- [Partitions](https://docs.ragie.ai/reference/list-partitions): Multi-tenant or logical isolation for scoped retrieval.
## Product & positioning
- [Homepage](https://www.ragie.ai/): What Ragie is, pipeline highlights, and links to SDKs/docs.
- [Pricing](https://www.ragie.ai/pricing): Plan tiers and us