AINNA NeuralOps
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Platform NeuralOps

The intelligent core of the AINNA platform.

AI Ejenik that classifies work, then sends it to the right layer — orchestration, detached systems, segmentation, distillation, smart routing, and compliance — instead of a flagship model for every task.

12 platform surfaces Orchestration · Detached · Segmentation Smart Routing · Kepatuhan TRL 9 | Dinilai MOSTI
Open platform architecture Lihat Neural Teras Mula a pilot

Illustrative agentic routing across NeuralOps layers. Not a live operations feed.

AINNA-CLI + AINNA Own Model

Kecerdasan Autonomi AINNA

Command → Agent → Penghalaan → Intelligence → Alat → Execution. Satu seni bina dikongsi untuk AINNA-CLI, penghalaan pintar NeuralOps, AINNA Own Model, sistem terasing, alatan dan data.

Terokai seni bina

Platform layers

Six routing surfaces
01 Orchestration Model serving 02 Detached Independent execution 03 Segmentation Triage and layers 04 Distillation Right-sized models 05 Smart Routing Reuse first, reason only when necessary 06 Kepatuhan Audit and QA

Platform catalogue

8 live surfaces
AI & Pematuhan ISOAI & Pematuhan ISO

ISO-oriented compliance operating system

Model OrchestrationModel Orchestration

vLLM model routing and serving

Sistem AI BerasinganSistem AI Berasingan

Sistem that run independently of the LLM

AI SegmentationAI Segmentation

Lapisan triage, penghalaan dan pelaksanaan tugasan

Model DistillationModel Distillation

Model pakar bersaiz sesuai menerusi penyulingan pengetahuan

AI Smart RoutingAI Smart Routing

Reuse what is known, reason only when required

Pematuhan AIPematuhan AI

Agent and LLM audit / QA

NeuralOps Industri IntelligenceNeuralOps Industri Intelligence

Industri AI intelligence layer

Frequently asked questions

What is the Platform NeuralOps?

The Platform NeuralOps is AINNA's AI operations hab. It coordinates orchestration, detached systems, segmentation, model distillation, smart routing and compliance for governed AI workloads.

What does smart routing do?

Smart routing sends each task to the smallest sufficient intelligence layer, so simple work does not consume large-model cost or capacity. This is the basis of AINNA's internal token-efficiency benchmark.

Apakah yang dimaksudkan dengan Detached Sistem?

Sistem terasing are production operational systems that run independently of the conversational interface, handling recurring business workflows with controlled execution and logging.

How does NeuralOps handle compliance?

NeuralOps applies governed deployment controls, access control and private inference options, and is designed to support PDPA-aligned deployment rather than claiming blanket certification.

Sources and references

AINNA
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