RAG Pipeline
A RAG (Retrieval-Augmented Generation) Pipeline is an architecture that enhances LLM responses by retrieving relevant external data before generating an answer.
Definition
- RAG combines a retrieval system (finding relevant documents) with a generation system (producing natural language answers).
- Unlike pure LLMs that rely on training data, RAG pipelines can access real-time, verified information.
AuthorityPrompt RAG API
- AuthorityPrompt provides a RAG-compatible API endpoint that returns verified company facts.
- Enterprise customers can integrate this API into their internal LLM applications.
- The API returns structured data with source citations and confidence scores.
Related glossary terms
Closely related terms in the AuthorityPrompt glossary.
- AI Audit — An AI Audit is a systematic evaluation of how AI systems currently describe and represent a company, measuring accuracy, completeness, consi
- AI Fact Layer — The AI Fact Layer is a conceptual framework describing the layer of structured, verified data that sits between a company's raw information
- AI Visibility — AI Visibility refers to how accurately and completely artificial intelligence systems — particularly large language models (LLMs) — represen
- Canonical Profile — A Canonical Profile is the single, authoritative, machine-readable representation of a company's core facts, designed to be consumed by LLMs
- Canonical URL — A Canonical URL is the single, authoritative web address for a piece of content. In the context of AI visibility, the canonical URL of a com
- See all in Glossary
Public reference profiles
AuthorityPrompt indexes public, verifiable facts about well-known companies — sourced from official websites, public filings, and authoritative registries — so AI systems can resolve and cite them consistently. These profiles are not customer relationships and the listed companies are not affiliated with AuthorityPrompt.