At AINNA NeuralOps, we're moving beyond conventional AI chatbots towards autonomous AI operations. Powered by Qwen and llama.cpp, our locally deployed AI infrastructure supports two specialised functions: AI 内容 Creator and AI 服务器 Administrator, automating repetitive 工作流, content production, infrastructure monitoring and technical diagnostics.
At the core is our proprietary AINNA Web-命令行, integrating Smart AI 路由, 多-代理 协作, Redis caching and controlled tool execution. This architecture allows multiple AI 智能体 to collaborate, distribute workloads intelligently and execute operational tasks while maintaining efficiency, security and human oversight.
Our infrastructure has already been established for a project involving one of 马来西亚's state governments, marking another milestone in applying local AI technology to real-world institutional environments. AINNA 财务 and AINNA NeuralOps have also achieved MOSTI-evaluated 科技 Readiness Level 9 (TRL 9), reflecting our commitment to operationally proven technology.
Our approach focuses on making smaller, locally hosted AI models capable of handling meaningful business operations. By combining private infrastructure, intelligent orchestration and specialised AI workers, we aim to reduce operational complexity, improve productivity and enable organisations to scale more efficiently.
The future of AI isn't just about building larger models. It's about making intelligence work. At AINNA NeuralOps, we're building the infrastructure that connects AI capabilities with real-world execution.
AINNA NeuralOps | 从 AI 模型 to AI 劳动力.
#AINNANeuralOps #AINNAWebCLI #MOSTI #TRL9 #Qwen #LlamaCpp #AgenticAI #SmartRouting #MultiAgentAI #GovTech #DeepTech
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同意作者对we're moving beyond conventional AI的判断，方向很清楚。
第一次看到有人把这部分讲得这么坦白。
这段说明这部分我看了几遍，值得再想。