Building a production RAG stack means handling file parsing, chunking strategies, embedding models, vector storage, retrieval tuning, prompt engineering, and observability. Docubix packages all of this into a hosted RAG platform with developer-friendly APIs — so you focus on product, not ML ops.
What's included
A complete RAG pipeline as a service.
- Document ingestion (PDF, DOCX, TXT, MD)
- Chunking, embedding, and vector indexing
- Cosine similarity retrieval with score thresholds
- LLM generation with configurable prompts
- Citation metadata on every response
When to use a hosted RAG platform
Self-hosting makes sense at massive scale. For most SaaS MVPs and support tools, a hosted RAG platform like Docubix gets you to production weeks faster.
FAQ
- What is a RAG platform?
- A RAG platform provides managed retrieval-augmented generation — document ingestion, embedding, search, and LLM answering — typically via API.
- Which embedding model does Docubix use?
- Docubix manages embedding and LLM configuration server-side. You configure retrieval and generation settings per knowledge base.
- Can I use Docubix RAG in production?
- Yes. Generate scoped API keys, set rate limits per knowledge base, and monitor usage from the dashboard.
Try the Docubix RAG platform
Free tier available. Upload a doc and query it via API in minutes.
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