Customer support · Production
Alibaba Cloud Higress intelligent diagnostic system resolves over 95% of consulting issues and over 85% of anomalies using multi-agent AI
The problem
Building effective AI agents requires integrating multiple data sources, maintaining high-quality domain data, and ensuring reliable performance that meets customer SLA requirements.
Workflow diagram · grounded in source
1
Customer data collection
trigger
“each application should collect and consolidate personalized and specialized data from customers”
2
Multi-source data integration
integration
“Higress is Alibaba's open-source AI-native API gateway, equipped with the most comprehensive AI ecosystem plugins, capable of helping developers integrate multiple data sources with a single click”
3
Reasoning effectiveness analysis
validation
“Based on the Otel observation system, we can automatically analyze the effectiveness of reasoning processes and recall results. If performance is subpar, we can trace the entire customer search and reasoning processes through an end-to-e…”
4
Dynamic prompt optimization
feedback_loop
“through Nacos, we can enable dynamic real-time pushing, obtaining timely optimization effects. If concerns arise post-launch regarding prompt changes, we can use gray configuration to gradually monitor the prompt data optimization effects”
5
Real-time data synchronization
integration
“We can sync change events and data in real-time through RocketMQ, ensuring that the most timely data and effects are available for each inference”
6
Diagnostic issue resolution
output
“solving over 95% of consulting issues and over 85% of anomalies”
Reported outcome
The intelligent diagnostic system built with Higress, Spring-AI-Alibaba, and MSE solves over 95% of consulting issues and over 85% of anomalies.
Reported metrics
Consulting issues resolvedover 95%
Anomalies resolvedover 85%
Reported stack
HigressSpring-AI-AlibabaNacosRocketMQOtelMicroservices Engine (MSE)DeepSeekRAGQuark
Source
https://www.alibabacloud.com/blog/development-trends-and-open-source-technology-practices-of-ai-agents_602037
Read source ↗Frequently asked questions
What did this team achieve with this AI workflow?
The intelligent diagnostic system built with Higress, Spring-AI-Alibaba, and MSE solves over 95% of consulting issues and over 85% of anomalies.
What tools did this team use?
Higress, Spring-AI-Alibaba, Nacos, RocketMQ, Otel, Microservices Engine (MSE), DeepSeek, RAG, Quark.
What results were reported?
Consulting issues resolved: over 95%; Anomalies resolved: over 85% (source-reported, not independently verified).
How is this customer support AI workflow structured?
Customer data collection → Multi-source data integration → Reasoning effectiveness analysis → Dynamic prompt optimization → Real-time data synchronization → Diagnostic issue resolution.