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Response Suggester Agent
by Internal Labs
0
Agent Template
<100
Summary
Summary
The Response Suggester is designed to draft accurate, citation-backed replies to customer tickets by detecting intent, retrieving relevant knowledge, and generating grounded responses.
Overview
Overview
Support teams often spend too much time researching articles and drafting repetitive replies. This slows resolution times, reduces consistency, and risks incorrect or outdated responses. The Response Suggester addresses this by analyzing incoming ticket text, detecting both the language and intent, and retrieving the most relevant knowledge snippets.
The agent generates a draft_reply grounded only in retrieved knowledge base content, with source_citations that include article IDs and URLs for transparency. When confidence is low or key details are missing, it provides a fallback promptasking the customer for clarification, ensuring accuracy and reducing escalation risk.
By automating first-draft responses, this agent reduces handle time, improves consistency, and enables support agents to focus on complex cases while still delivering high-quality, well-referenced answers.
Features
Features
- Purpose-built agent definition for support response drafting
- Automated detection of ticket language and intent
- Retrieval-augmented generation (RAG) using knowledge base content
- Draft replies grounded in real snippets with source citations
- Fallback mode for low-confidence cases to request missing details
- Best practices built in for reliability and compliance
- Prebuilt tools for quick deployment and customization
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