# Perplexity — What Is RAG Architecture? Definition and Examples

- Company: Perplexity (perplexity.ai)
- Announced: 2026-10-26
- Category: not stated
- Coverage: not counted
- Announcement: no
- Group: routine
- Source: https://www.perplexity.ai/hub/blog/rag-architecture
- Record: https://forck.live/items/27955-what-is-rag-architecture-definition-and-examples
- Subject: Perplexity

Perplexity's explainer sets out what RAG architecture is and walks through the main variants, describing RAG as a process in which LLMs use external information to expand on and improve their outputs. It lays out the foundational template, often called simple or naive RAG, built from an information source, a retrieval component and an orchestration layer that compiles retrieved text into an expanded prompt. The piece splits the components into an ingestion path, which organizes data into a searchable source such as a vector database, and a retrieval path, which turns a user prompt into a query and adds the results to the LLM's context. It then covers hybrid RAG, which combines keyword and semantic retrieval and may rerank merged results before passing them to the model, and adaptive RAG, where a routing component picks a retrieval strategy based on the prompt. Corrective RAG is described as evaluating retrieved information before it reaches the model, triggering further requests when the material is incomplete or not applicable. The explainer cautions that treating RAG types as completely distinct architectures is misleading, since most engineers implement separate components modularly and the models overlap significantly.

## Evidence

Verbatim from https://www.perplexity.ai/hub/blog/rag-architecture:

> RAG, which stands for retrieval augmented generation, is a process in which LLMs use external information to expand on and improve their outputs. RAG architecture is the set of components and connections that makes RAG possible.
> 
> There are several different categories of RAG, and each one runs on its own unique architecture. In essence, the architecture of a RAG system determines the unique way in which information is stored, retrieved, and fed to an LLM.
> 
> What is RAG architecture?
> 
> RAG architecture is the underlying configuration of components (and their associated capabilities) that powers a given RAG system. All of these architectures build on a foundational template, often referred to as "simple" or “naive” RAG.
> 
> Here’s a high-level overview of foundational RAG architecture:
> 
> Information source: This is where the external information is stored. It might be a search index, a vector database representing large quantities of information, or a raw document repository.
> 
> Retrieval component: This is the mechanism by which the information source is queried.

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