Because we believe the future of AI untuk PKS is not just about access to powerful models. It is about making AI more affordable, more controllable, and more reliable in real operations.
Today, many AI alatan are impressive on the surface, but the financial challenges persist: multiple subscriptions, unpredictable token costs, workflows that don't match actual business processes, and heavy dependency on external vendors.
That is why we are building our own AI agen as a development layer. The goal is to let a founder, operator, teacher, site supervisor, or any domain expert describe a real problem and use AI to build a website, application, automation, or operational system-while keeping the jumlah cost of ownership in check.
At the same time, we are working on model distillation to create a lebih kecil, more focused model for practical PKS use cases. We are not trying to build the biggest model. We are trying to build one that is sufficient for the task, economical to run, simple to deploy, and controllable.
Our direction is straightforward:
Describe the problem → AI builds the system → PKS operates it.
For AI to deliver measurable value to PKS, it must be accessible, affordable, and operationally reliable-not just impressive in a demo.
That is why we are building our own stack-to manage costs, ensure reliability, and achieve financial predictability.
#AI #AgenticAI #AIAgent #LLM #ModelDistillation #PKS #Automasi #AINNA #NeuralOps #SovereignAI
Ruang pembaca
Apa pendapat anda?
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ensure reliability, and achieve financial - that is teh whole thing in one line.
I would push back slightly on application, automation, or operational, but the direction is right.
The figures on operator, teacher, site supervisor make more sense than most posts.
Bookmarked, mainly for multiple subscriptions, unpredictable token. Have a few questions left here.
Honestly economical to run, simple caught me off guard.
Not fully sold on workflows that don't match actual, but the rest is solid.
还在消化这段说明这一段。
First piece I have read that treats affordable, and operationally reliable-not honestly.