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This feature is only available in Fusion 5.9.x for versions 5.9.15 and later.
The Chunking RAG Bridge query stage extracts relevant snippets from source documents used in RAG responses. When your query pipeline includes document chunking and retrieval via the Chunking Neural Hybrid Query stage, this stage identifies and includes the most relevant chunk for each cited document in the response. When used in your query pipeline, searchers can validate the content of the AI-generated response by comparing the response with the relevant section of the source material.

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Example use cases for this stage

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B2B use case

A user asks, “What is the data retention policy for customer financial records?”

Before (document-level RAG)

RAG answer: Customer data is retained according to company policy and applicable regulations. Source: Enterprise Compliance ManualProblem: An entire manual with hundreds of pages is cited. The user still has to search the document to find the actual retention period and rules.

After (chunk-level RAG with snippets)

RAG answer: Customer financial records must be retained for 7 years in compliance with regulatory requirements. Source: Enterprise Compliance Manual ”…Section 4.2 — Financial records must be stored for a minimum of 7 years before secure archival or disposal…”Benefit: The answer is backed by the exact snippet from the compliance manual, so users can immediately validate and take action without reading through the full document.

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B2C use case

A user asks, “Does this laptop support international power adapters?”

Before (document-level RAG)

RAG answer: The laptop is compatible with standard accessories. Source: Product Specification SheetProblem: The entire product sheet is cited. The shopper still needs to scan through dozens of specifications to find the answer.

After (chunk-level RAG with snippets)

RAG answer: Yes, this laptop supports international power adapters (100–240V) and includes a universal charger. Source: Product Specification Sheet ”…Power Supply: 100–240V universal adapter included. Supports multiple regional plug types…”Benefit: The answer is precise and backed by the exact snippet from the source. The shopper can make a confident purchase decision without reading through unrelated details.

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Order of stage in a pipeline

You can pass on the response of this stage as the context field in the LWAI Prediction stage in order to generate relevant results and chunks for searchers. When using the Chunking RAG Bridge stage, it must be placed between the Chunking Neural Hybrid Query stage and the LWAI Prediction Query stage in your pipeline.

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Configuration

When entering configuration values in the UI, use unescaped characters, such as \t for the tab character. When entering configuration values in the API, use escaped characters, such as \\t for the tab character.
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