Not every business task carries the same financial weight.
That is why, at AINNA, we look at 智能路由 AI as a cost-control mechanism, not just a technical 设计.
Rather than routing every request straight to the most expensive AI model, the 系统 assigns work through a clear execution hierarchy:
规则 → 解析器 → 自动化 → SLM → LLM
高-volume, repetitive work should never consume premium inference capacity.
结构d transactions and rules-based processes should be settled deterministically.
Only judgement-heavy exceptions and complex reasoning should reach the larger models.
The 目标 is not to spend more on AI.
The 目标 is to match the right intelligence, to the right layer, for the right financial outcome.
For 马来西亚n 中小企业, this translates into lower token consumption, reduced compute load, faster closing and reconciliations, and more predictable monthly operating costs.
Classify first. Automate where possible. 升级 only when justified.
#SmartRouting #AI #AI基础设施 #AI自动化 #LLM #SLM #企业版AI #DigitalTransformation #中小企业 #Artificial智能
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视觉和结构让automate where possible的概念更容易掌握。
我特别喜欢rules-based这一部分，内容没有把实施过程说得太简单。
我会把cost-control这一段分享给需要了解技术的同事。
文章把judgement-heavy和日常运营联系起来，这一点很有帮助。
总结部分让结构d transactions and rules-based processes的重点更加清楚。
如果可以继续说明repetitive work should never consume的真实案例，我会想继续阅读。
这篇文章对结构d transactions and rules-based processes的解释很清楚，实际操作的重点也很容易理解。
关于cost-control的实际落地部分最吸引我。