Build a Chatbot with Cohere Citations

The Cohere Citations Chat Engine Pack provides a pre-built workflow for creating conversational AI systems that cite their sources. It wraps Cohere's citation-capable chat API into a LlamaIndex pack, enabling developers to deploy question-answering systems where every claim in the response is linked back to specific documents or passages. This eliminates the black-box problem common in many chat interfaces by making the reasoning transparent and verifiable.

Use this pack when you need to build customer-facing chat systems where trust and verifiability matter: legal research tools, medical information assistants, compliance documentation search, or any domain where users must trace answers back to authoritative sources. It is ideal when your knowledge base is document-heavy and users need to audit or verify the AI's claims.

Do not use this pack if your application does not require source attribution or if you need a chat system optimized purely for speed over transparency. If your use case involves highly creative or generative tasks where citation to source material is not relevant, a standard chat engine without citation overhead will perform better.

You provide a set of documents or a knowledge base that the system will reference, along with user queries in natural language. The pack handles the orchestration between your data, the Cohere API, and the citation logic.

You receive conversational responses where each statement or fact is accompanied by citations pointing to the specific source documents or passages that support it. This allows end users to click through and verify the information independently.

This pack is built for developers and AI engineers building enterprise search, knowledge management platforms, or customer support tools where accountability is non-negotiable. It suits teams working in regulated industries (healthcare, finance, legal) who must demonstrate how their AI arrives at conclusions. It differs from generic chat solutions by prioritizing explainability and audit trails over raw conversational fluency.