> ## Documentation Index
> Fetch the complete documentation index at: https://docs.alquimia.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Topics and documents

> How topics and documents work together as InsightHub's core building blocks.

Everything in InsightHub is organized around two building blocks: **topics** and **documents**.

## Topics

A topic represents a knowledge domain — a subject area you want to explore. It is the container for a set of related documents and the entry point for starting explorations.

A well-scoped topic makes exploration answers more precise because the AI searches within a bounded, relevant set of documents. Rather than putting everything into one topic, create separate topics for distinct domains:

* "Product specs — v2.3"
* "Q4 investor materials"
* "Customer onboarding guides"

## Documents

Documents are the source material inside a topic. When you upload a file, InsightHub processes it into a form the AI can work with:

```
Upload
   ↓
Text extraction
   ↓
Chunking (split into passages)
   ↓
Embedding (passages converted to vectors)
   ↓
Indexed in the vector store
```

When the AI answers a question during an exploration, it searches these indexed passages — not the raw files. The answer is assembled from retrieved chunks, not recalled from general training knowledge.

## How they shape exploration answers

The AI during an exploration only has access to documents within the current topic. This means:

* **Answers are scoped** — the AI answers from your documents, not general knowledge alone
* **Boundaries matter** — if a relevant document is not in the topic, the AI cannot reference it
* **Document quality counts** — clean, on-topic files improve retrieval accuracy

<Tip>
  If an exploration answer seems incomplete or off-target, check that the relevant documents are uploaded, fully processed (**Ready** status), and belong to the correct topic.
</Tip>

## Next steps

<Card title="RAG" icon="search" href="/products/insight-hub/core-concepts/rag">
  Understand how the AI retrieves and uses document passages to answer questions.
</Card>