We submit a system description paper for SemEval-2026 Task 8 (MTRAGEval), covering both Subtask A (retrieval) and Subtask B (generation). Our approach is a lightweight, fully reproducible multi-turn RAG pipeline using open-weight models: Qwen2.5-7B-Instruct for query rewriting and grounded answer generation, BGE-M3 for dense retrieval, and BGE-Reranker-v2-M3 for cross-encoder reranking. We report official test performance, conduct ablation experiments to quantify the impact of rewriting and reranking across domains, and provide error analysis using the organizers’ analytics and answerability classes, highlighting key failure modes in multi-turn retrieval specificity and grounded generation.