Introduction: The Turning Point from Dispersed Traffic to Intelligent Governance

Since early 2025, within a leading global appliance giant, multiple business lines have introduced numerous large language models (LLMs). The R&D department needed coding assistants to improve efficiency, the marketing team focused on content generation, and the smart product team aimed to integrate conversational capabilities into home appliances. The variety of models rapidly expanded to include both self-built solutions like DeepSeek and Qwen, as well as proprietary models from multiple cloud service providers.

However, this rapid expansion soon exposed new bottlenecks: fragmented inference traffic, chaotic scheduling, rising operational costs, and uncontrollable stability issues.