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An Auditable Symbolic-RAG-Generative AI Architecture for Goal-Oriented Conversation Orchestration

arXiv · AI, language, vision and robotics · article · Sep 7, 2026 · UTC

Goal-oriented conversational systems must answer factual questions, understand visitor-provided information, and advance business objectives without becoming rigid questionnaires. This paper proposes a Symbolic-RAG-Generative architecture centered on the Goal-oriented Retrieval-Augmented Conversation Engine (GRACE). An instruction-constrained Business Goal Compiler transforms business intent into an immutable objective set, normalized priority vector, canonical questions, and initial state vector. At runtime, GRACE receives the complete conversation history, latest visitor message, current sta

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Evidence & attribution

First collected: 2026-09-20T20:52:10.320Z. This is not the publication date.