Ragie.ai has officially launched its RAG-as-a-service platform with $5.5M in seed funding

Ragie.ai has launched a new way in which developers can quickly build AI-powered applications that leverage private data to deliver more relevant results. The novel RAG-as-a-Service platform was founded by industry veterans Bob Remeika and Mohammed Rafiq and aims to provide an alternative to the popular method which involves combining foundation models from providers such as OpenAI and Anthropic with RAG techniques to build AI applications. Although RAG delivers outstanding results, developers must transform their raw data into a vector database before inputting it with a prompt.

The Ragie platform was built to prove that a robust data pipeline can save developers' time and improve the resulting applications. By offering developers a ready-to-use data ingest platform and retrieval API that leverages the latest techniques for chunking, searching, and re-ranking and that can integrate with popular data sources like Google Drive, Notion, and Confluence, Ragie provides a fully managed RAG-as-a-service platform. The platform offers advanced features: a summary index creation feature to implement two-tiered indexing (with one index spanning document chunks and the other document summaries), and an entity extraction capability that lets users extract structured data from unstructured documents.

Ragie's pricing includes a free tier with a 500 document and 10 requests per minute limit, a $500 monthly Pro subscription that enables applications to go into production by offering a 3,000 document and 1,000 requests per minute limit, and a customizable enterprise plan, priced according to the resources needed. To celebrate Ragie's launch, a free 1-month trial of the Pro plan will be available for a limited time.