Sovereign IIoT & Agentic AI Platform

Bridging OT and IT with Strictly On-Premise Intelligence

Our specialized capability ensures an airtight, localized environment where raw sensor data meets real-time video analytics and Agentic AI without ever leaving your facility.

The CognusOps Advantage

While many platforms rely on cloud dependencies, our IIoT foundation is built strictly for on-premise data sovereignty.

Leveraging our deep in-house engineering expertise in PLC, SCADA, and DCS systems, we eliminate the traditional barriers between the factory floor and enterprise IT.

We don't just provide software; we provide the control engineering required to seamlessly connect sensors, edge devices, and legacy machinery to modern IT protocols like OPC UA and MQTT.

Core Mission

  • Strict on-premise data sovereignty.
  • Deep in-house engineering expertise in PLC, SCADA, and DCS.
  • Seamless connection of legacy machinery to modern IT protocols (OPC UA, MQTT).
System Blueprint

Sovereign OT-IT Architecture

A simplified 4-layer representation of our strictly air-gapped, zero-trust industrial network blueprint.

Layer 1

Local IT & Enterprise

Strictly On-Premise

MES

Manufacturing Execution

ERP

Resource Planning

Data Historian

Sovereign Portal
Layer 2

Private Local Server

Intelligent Multimodal Hub

REST/MQTT API

Agentic AI Hub

  • • Multimodal Data Fusion
  • • Generative Scene Desc.
  • • Workflow Planning

Unified Namespace

  • • MQTT over TLS
  • • Real-Time Exchange
  • • Local Time-Series

Central Mgmt

  • • Edge & Security Gov.
  • • Data Workflows
Layer 3

Industrial Edge

Filtering & Edge AI

MQTT / Fused Data

Video AI Nodes

Streams Pre-process Object Detect

Edge Gateways

  • • Modbus/Profinet Ingest
  • • CV Meta Aggregation
Agentic Control Loop to PLCs
Layer 4

OT Assets & Devices

The Factory Floor

OPC UA / Control Loop
PLC Controls
CNCs
Robots
⚙️ Motors
Valves
CCTV

Agentic AI & Analytical Hub

At the core of the local server layer sits our Intelligent Reasoning Hub, designed to process both operational data and high-bandwidth video streams on-premise.

Rule-Based & Predictive Alerting

Real-time threshold monitoring with automated dispatch of security or operational alerts.

Multimodal Data Fusion

Synchronizing structured OPC UA data with unstructured video metadata to provide profound context (e.g., matching a pressure drop with video evidence of a valve leak).

Autonomous Closed-Loop Control

Agentic workflows that don't just alert, but actively execute control commands back to the PLC (e.g., halting production or adjusting VFD speed) based on generative scene analysis.

Upstream AI Connectivity

Ready for seamless integration with robust, white-labeled video analytics and localized LLMs.

IIoT Implementation Best Practices

1. Edge-Heavy Processing

Execute data filtering, transformation, and high-intensity tasks (like video analytics) directly at the Edge Node. Only push synthesized metadata and critical anomalies to the central server layer to conserve local network bandwidth.

2. Unified Namespace (UNS)

Utilize MQTT over TLS as a central nervous system. Establish a standardized data hierarchy across the enterprise so all devices and applications produce and consume data from a single source of truth.

3. Zero-Trust Security

Air-gap the IT and OT networks physically or logically. Implement strict role-based access control (RBAC), secure encrypted communications (MQTT/TLS), and rely entirely on on-premise components to maintain absolute data sovereignty.

4. Actionable Data

Leverage the platform's drag-and-drop workflow engine to validate and contextualize data *before* storage. Prevent "data swamps" by ensuring every piece of ingested data has operational context and is linked to specific assets or processes.