RAG-as-a-service API for developers. Connect your data, get a retrieval endpoint in minutes — not weeks.
Building retrieval-augmented generation from scratch means choosing embeddings, a vector DB, a chunking strategy, a reranker, a retrieval API, and an eval pipeline — that's a 2-week project minimum, more if you care about correctness. Ragie wraps all of it in a single hosted API: upload your PDFs, Notion, Google Drive, or raw text, and you get a retrieval endpoint with citations, multi-modal support, and streaming responses. It's the "Stripe for RAG" pitch, and it largely delivers.
Who it's for: Founders and full-stack engineers shipping a chatbot, support assistant, or "ask your data" feature without a dedicated ML team. Also a strong fit for internal-tool builders who want RAG without maintaining Pinecone + LangChain glue.
One-click syncs for Google Drive, Notion, Confluence, Slack, and more. Auto-reindexes on source changes — no manual refresh pipeline to babysit.
Every answer comes back with source spans linked back to the original document chunk. Critical for support/legal/compliance use cases where hallucinations cost money.
Ragie extracts text from tables, charts, and images inside PDFs — not just plain paragraphs. Most DIY RAG setups choke on the same documents Ragie handles out of the box.
Official JavaScript/TypeScript and Python SDKs with a 5-line "chat with your data" example. Bring your own LLM key or use Ragie's hosted models.
If your business isn't "we built a better RAG pipeline," you probably shouldn't be building one. Ragie lets you ship the chatbot-your-data feature this week, and switch to a DIY stack later only if usage economics demand it. For 90% of teams, that trade is a no-brainer.
The framework for building RAG and LLM apps from scratch. Maximum control, more work.
Managed vector database. The storage layer under many DIY RAG setups.
Open-source data framework for LLMs. The other big "build your own RAG" option.
Another end-to-end hosted RAG platform. Ragie's closest direct competitor.