A managed RAG-as-a-Service platform that provides a single API or deployable starter kit handling document ingestion (PDFs, URLs, web scraping), automatic chunking and embedding, vector storage, retrieval with source citations, and multi-file support. Developers plug in their LLM provider and focus entirely on their product's unique value.

The explosion of LLM-powered apps has made RAG the default architecture for document-grounded AI, yet the tooling remains fragmented and boilerplate-heavy. Developers are actively seeking productized shortcuts as the market shifts from experimenting with AI to shipping production SaaS products quickly.