SOURCE-LINKED INTELLIGENCE
RAFT: A Stateful Retrieval-Augmented Framework for Troubleshooting Agents
Effective troubleshooting agents in enterprise customer support depend on retrieving actionable guidance from similar historical cases, yet existing retrieval-augmented generation (RAG) systems treat support cases as static documents and overlook their multi-stage, stateful nature. We introduce RAFT (Retrieval-Augmented Framework for Troubleshooting Agents), a stateful RAG framework that abstracts each closed historical case into a directed chain of timeline entries and retrieves at the entry level, surfacing cases whose intermediate states match the active case and returning the parent-case t
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-17T17:41:31.000Z
- arXiv · Artificial Intelligence · 2026-09-17T17:41:31.000Z
First collected: 2026-09-19T20:26:32.566Z. This is not the publication date.