Conversational RAG
Build conversational experiences that interact with your organizational documents.
Overview
Conversational RAG allows you to build multi-turn, chat-based experiences that interact with your enterprise documents and data. Built on top of AI21’s advanced RAG Engine and infused with a planning layer, it enables users to ask follow-up questions and receive grounded, context-aware answers.
Conversational RAG ensures accurate, high-quality answers that reflect your proprietary knowledge base.
Key Benefits
Chat with Your Data
Go beyond single-question answering by allowing follow-up questions, clarifications, and step-by-step problem-solving through a natural conversation.
Enterprise-Grade Accuracy
Built on retrieval-augmented generation (RAG), responses are grounded in your actual documents, not just model hallucination. It’s useful for internal tools and customer-facing applications alike.
Fully Managed & Easy to Deploy
Simply upload your documents (PDF, DOCX, TXT, HTML, or Markdown). The RAG Engine automatically indexes them, making setup fast and seamless. Data connectors are coming soon.
Product Details
Conversational RAG is a compound AI system that uses a planning module to assess incoming queries. It chooses whether to respond solely using LLMs, or route the query to the RAG Engine to retrieve grounded context before generating a response.
This hybrid architecture ensures quality, visibility, and flexibility across a range of enterprise applications.
Input/Output Modalities
Input: Designed for multi-turn text conversations that reference your enterprise documents. This is the primary use case that delivers the most value through grounded, contextual responses. While designed for interactive dialogue with your data, the system can still handle other types of inputs (e.g., single-shot queries).
Output: Grounded, context-aware responses.
Deployment & Document Ingestion
- Upload supported document types: .pdf, .docx, .txt, .md, .html.
- Indexing is automatic.
- The conversational RAG system includes our in-house document parser, which provides high-quality parsing.
- Data connectors to cloud sources.