Production-level Multilingual Customer Service Agent
A desensitized project note about building multilingual LLM agents for overseas customer-service scenarios.
Role: Agent workflow, data construction, evaluation, and behavior optimization
Confidentiality: Company names, product names, internal APIs, and sensitive metrics are removed.
Problem
Traditional FAQ systems and rule-based bots struggle when users express long-tail issues in different languages.
The challenge is not only language translation. A useful customer-service agent must understand intent, retrieve domain knowledge, use tools when needed, and remain stable across multi-turn context.
My Role
I worked on agent workflow design, data construction, evaluation, and behavior optimization.
Approach
The system combined several components:
- Domain knowledge organization
- Retrieval and prompt grounding
- Tool-use boundaries
- Multilingual response control
- Failure-case analysis
- Iterative evaluation
Impact
The agent improved support quality in multilingual scenarios. Sensitive business details are omitted here.
What I Learned
Reliable agents are not only about stronger models. They need clear tool boundaries, good evaluation data, controlled memory, and systematic failure analysis.