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Research · Intermediate

# Semantic knowledge base search and synthesis

Query internal document collections using vector retrieval to synthesize research findings

[Use with BotBento ](https://app.botbento.com/?ref=usecases&utm_source=botbento.com&utm_medium=usecases&utm_campaign=semantic-knowledge-base-search-and-synthesis)Copy promptShare[Markdown](/text/usecases/semantic-knowledge-base-search-and-synthesis/index.md)

Opens BotBento. Paste the prompt into a bot; nothing is preconfigured.

- When you askUser submits research query
- ThenRetrieve matching document chunks
- ResultSynthesized brief with sources

Perform semantic search across document stores to uncover relevant context for complex research topics. The bot queries indexed embeddings to extract matching passages, cross-references source metadata, and compiles an organized brief summarizing the most pertinent information.

## Prompt to start with

BotBentoRecommended

```
When a research inquiry is submitted in chat, query the vector database to locate relevant document excerpts and metadata. Synthesize the retrieved excerpts into a coherent topic brief with citations. Do not delete or overwrite any stored database records without explicit user confirmation.
```

Copy

## Tools it uses

ChatDatabaseDocs

## Works with

BotBento

## Tags

- search
- embeddings
- knowledge-base
- retrieval

## Source

[chroma: Search infrastructure for AI](https://github.com/chroma-core/chroma)
GitHub · checked 2026-10-15

Summarized in our own words. Any results described there are the authors’ own, not measured by BotBento.

By BotBento Editorial · Added 2026-10-15 · Updated 2026-10-15 · [Suggest a correction](/contact/)

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