The AgentForce Retriever Configuration Guide specifies that filters are used to refine and constrain search results within a retriever setup. Filters operate by applying conditions (up to 10) on indexed fields such as document type, category, region, or update date. This targeted filtering ensures that the retrieved data is highly relevant to the current user query or context.
For instance, an AgentForce retriever could be configured to include only documents tagged as “Active” or within a specific product line, reducing noise and improving grounding accuracy for the LLM. This mechanism supports precision retrieval, which directly improves both the accuracy and reliability of generated responses.
Option B is incorrect because filters do not handle encryption or masking of sensitive data — those functions are managed through Data Cloud security and access controls. Option C is incorrect because retrievers do not aggregate or summarize documents; they retrieve data for grounding, leaving summarization to the LLM reasoning layer.
Therefore, the correct answer is Option A – Filters narrow search results using field-based conditions to improve relevancy and retrieval precision.
[Reference: AgentForce Implementation Guide — “Configuring Filters for Targeted Retrieval in Custom Retriever Settings.”, , , , , , ]
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