AINNA NeuralOps
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NeuralOps Platform

The intelligent core of the AINNA platform.

Agentic AI 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 · Compliance TRL 9 | MOSTI Assessed
Open platform architecture View Neural Core Start a pilot

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

AINNA-CLI + AINNA Own Model

AINNA Autonomous Intelligence

Command → Agent → Routing → Intelligence → Tools → Execution. One shared architecture for AINNA-CLI, NeuralOps smart routing, AINNA Own Model, detached systems, tools and data.

Explore architecture

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 Compliance Audit and QA

Platform catalogue

8 live surfaces
AI & ISO ComplianceAI & ISO Compliance

ISO-oriented compliance operating system

Model OrchestrationModel Orchestration

vLLM model routing and serving

Detached AI SystemsDetached AI Systems

Systems that run independently of the LLM

AI SegmentationAI Segmentation

Task triage, routing and execution layers

Model DistillationModel Distillation

Right-sized specialist models via knowledge distillation

AI Smart RoutingAI Smart Routing

Reuse what is known, reason only when required

AI ComplianceAI Compliance

Agent and LLM audit / QA

NeuralOps Industrial IntelligenceNeuralOps Industrial Intelligence

Industrial AI intelligence layer

Frequently asked questions

What is the NeuralOps Platform?

The NeuralOps Platform is AINNA's AI operations hub. 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.

What are detached systems?

Detached systems 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

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