Not every business task carries the same financial weight.
That is why, at AINNA, we look at Smart Routing AI as a cost-control mechanism, not just a technical design.
Rather than routing every request straight to the most expensive AI model, the system assigns work through a clear execution hierarchy:
Rules → Parser → Automation → SLM → LLM
High-volume, repetitive work should never consume premium inference capacity.
Structured transactions and rules-based processes should be settled deterministically.
Only judgement-heavy exceptions and complex reasoning should reach the larger models.
The objective is not to spend more on AI.
The objective is to match the right intelligence, to the right layer, for the right financial outcome.
For Malaysian SMEs, this translates into lower token consumption, reduced compute load, faster closing and reconciliations, and more predictable monthly operating costs.
Classify first. Automate where possible. Escalate only when justified.
#SmartRouting #AI #AIInfrastructure #AIAutomation #LLM #SLM #EnterpriseAI #DigitalTransformation #SME #ArtificialIntelligence
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Berbaloi baca sebab automate where possible.
Bahagian automate where possible tu yang buat saya fikir lama.
Useful. We are dealing with cost-control right now.
First piece I have read that treats rules-based honestly.
The section on automate where possible is the strongest part for me.
Bookmarked, mostly for repetitive work should never consume.
We hit structured transactions and rules-based at work before. Good that someone wrote it down.
judgement-heavy is what I would forward to my boss.