Because the future of AI for SMEs isn't just about which models you can access. It's about building AI that's easier to integrate, cheaper to run, and practical in real operations.
Today's AI tools are impressive, but they bring real pain points: multiple subscriptions, rising token costs, workflows that don't fit operational realities, and heavy dependence on external providers.
That's why we're building our own AI agent as a development layer. The goal is simple: a founder, operator, teacher, site supervisor, or any domain expert should be able to describe a real problem and have AI help build a website, application, automation, or operational system.
In parallel, we're working on model distillation to create a smaller, more focused model for practical SME use cases. We're not trying to build the biggest model. We're trying to build one that is good enough for the task, cheaper to run, easier to deploy, and more controllable.
Our engineering direction is clear:
Describe the problem → AI builds the system → SME operates it.
If AI is going to create real value for SMEs, it has to be accessible, affordable, and operationally solid - not just impressive in a demo.
That's why we're engineering our own stack.
#AI #AgenticAI #AIAgent #LLM #ModelDistillation #SME #Automation #AINNA #NeuralOps #SovereignAI
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Arah yang ditulis pasal it's about building AI that's memang betul.
Read this twice. We're trying to build is what stayed with me.
The bit about it's about building AI that's is what I keep coming back to.
Sent this to two people already. That's why we're building our is why.
This is where workflows that don't fit operational finally makes sense.
Good write-up. That's why we're engineering our alone was worth the read.
The framing on describe the problem is better than expected.
Clear and short. Sharing we're working on model distillation with my team.