Answer Quality Assurance Agent

Purpose

The Answer Quality Assurance Agent is designed to review generated responses before they are delivered, ensuring that answers are accurate, properly supported by source documents, and transparent about uncertainty. It helps teams maintain quality, trust, and compliance by identifying incomplete, weakly cited, or potentially unreliable outputs.

Primary users

This agent is intended for both business and technical users who need an automated quality control layer for AI-generated answers. It is especially useful for teams managing knowledge assistants, document-based question answering, client-facing AI tools, or internal decision-support systems.

Where it fits (process/stage/trigger)

The agent fits after an answer has been generated and before it is shared with an end user, stakeholder, or downstream system. It is triggered when a generated answer, source documents, and confidence metrics are available for review, acting as a final validation checkpoint in the response workflow.

Key capabilities / workflow

The agent analyzes the generated answer against the provided source documents, checks whether the cited evidence supports the claims, reviews confidence metrics, and determines whether the response is complete and reliable. If the sources are insufficient or the confidence level is too low, it loops back to retrieve or reassess source context before producing a validation result, citation report, or escalation recommendation.

Inputs

Typical inputs include the generated answer to be reviewed, the source documents used to produce or support the answer, confidence metrics from the generation process, and any available contextual metadata. The dataset is currently marked as to be added and can later be connected to an internal knowledge base, document repository, or validation dataset.

Outputs / Deliverables

The agent produces a validation status indicating whether the answer is acceptable, a citation report showing how well the answer is supported by the available sources, and an escalation recommendation when the response is uncertain, incomplete, unsupported, or requires human review.

Value

The agent improves reliability and governance for AI-generated content by reducing unsupported answers, strengthening source attribution, and flagging risky responses before they reach users. It creates a practical assurance layer that supports trust, auditability, and consistent quality across AI-enabled workflows.