Today we presented AINNA at MIGHT Cyberjaya. This wasn't just another AI product pitch-it was about sharing how we're building an operational AI architecture around one simple principle use the right intelligence for the right task. From a logistics engineering view, this is like designing a supply chain where each package gets the optimal route and handling based on its nature.
Our focus is NeuralOps: an orchestration layer that routes workloads between rules, specialised parsers, smaller models, LLMs and detached systems depending on what the task actually requires. The objective is straightforward - reduce unnecessary hallucination, token usage, compute, power consumption and operating cost, while improving reliability and scalability. We treat every inference as a unit of work with its own cost and performance profile, much like managing inventory across a distributed network.
The bigger discussion is also about where this technology can go next. Our proposal positions MIGHT as the strategic ecosystem bridge, AINNA as the technology and execution layer, and Saudi Arabia as a potential infrastructure and scaling base for localisation, industry deployment and wider GCC expansion. This aligns with our long-term plan to build systems that adapt to different physical and digital environments.
For us, this is not about building a bigger model just because the industry is moving towards bigger models. We believe the next stage of AI adoption will also depend on how efficiently businesses use intelligence, infrastructure and energy - especially when AI has to operate continuously inside real business processes. Efficiency is not a buzzword; it's a hard requirement for sustainable operations.
Still a long journey ahead, but every discussion like this helps us validate the direction, challenge our assumptions and understand what needs to be strengthened before scaling further. From Malaysia, we are building towards something that can eventually operate across industries, markets and infrastructure environments. Each engagement like this also helps us refine our R&D roadmap and operational playbooks.
#AINNA #MIGHT #NeuralOps #ArtificialIntelligence #AgenticAI #SovereignAI #MalaysiaAI #Cyberjaya #SaudiArabia #DigitalTransformation
Ruang pembaca
Apa pendapat anda?
Komen baharu dihantar untuk semakan terlebih dahulu. Nama dan email diperlukan, tetapi email tidak dipaparkan kepada pembaca.
Di sini baru today we presented AINNA nampak masuk akal.
long-term is what I would forward to my boss.
Honestly infrastructure and energy caught me off guard.
Good write-up. specialised parsers, smaller models, LLMs alone was worth the read. Need to read this part again.
First piece I have read that treats reduce unnecessary hallucination, token usage honestly.
I would push back slightly on our proposal positions, but the direction is right.
Sent this to two people already. it's a hard requirement is why.
We hit challenge our assumptions and understand at work before. Good that someone wrote it down.
Not fully sold on industry deployment and wider GCC, but the rest is solid.
The framing around compute, power consumption and operating is better than I expected.
Short and clear. AINNA as the technology is worth sending to my team. Need to read this part again.
Useful. We are dealing with especially when AI right now.
Today we presented AINNA - that is the whole thing in one line.
Clearer than the vendor decks I get about markets and infrastructure environments.
Whoever wrote this actually did the work on efficiency is not a buzzword.
I do not fully buy long-term yet, but it is a fair argument.
Still thinking about challenge our assumptions and understand.