Our Technology

The infrastructure behind
intelligent operations.

A platform that connects, models, analyses, and acts — across any operation, at any scale, in real time.


Operational Flow

How It Works

01

Connect

Link any data source, sensor, IoT device or system.

02

Model

Build your digital twin with no-code tools.

03

Analyse

AI monitors every process in real time automatically.

04

Act

Receive alerts and recommendations before problems escalate.

01 — Connect

Link any data source, sensor, IoT device or system.

The first step is bringing all your data into one place. Our platform connects to any source with a digital interface — without replacing your existing infrastructure. Whatever systems you already have, we link to them. Data flows continuously from every connected source into a unified real-time data layer — normalised, timestamped, and ready for processing.

All communication is encrypted end-to-end using HTTPS and secure WebSocket protocols compliant with ISO/IEC 18033-3. Supported protocols: MQTT · CoAP · RESTful HTTP/HTTPS · OPC UA · WebSockets · LoRa · 4G/5G · Wi-Fi · LAN/WAN

About Security

What we connect to:

  • — IoT sensors and smart meters of any type
  • — Industrial control and automation systems (SCADA, PLC, DCS)
  • — Building automation systems via BACnet, Modbus, KNX gateways
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02 — Model

Build your digital twin with no-code tools.

Once data is flowing, we build a structured digital model of your system — its objects, processes, hierarchy, interdependencies, and operational logic. This is your digital twin: a live computational representation of your real-world operation. What happens at this stage:

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System hierarchy

Your system is mapped as a hierarchy of objects — buildings, production lines, districts, assets, departments — each with defined properties, states, and relationships.

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Visual KPI Editor

Performance indicators (KPIs) are defined using a visual Indicator Editor — formulas linked directly to live data streams, with no programming required.

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Operational targets

Operational targets, thresholds, and sustainability rules are configured for each object and process.

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Standards compliance

International standards are embedded into the model as compliance targets — ISO 37120, ISO 50001, ISO 14001, ISO 9001, and others relevant to your domain.

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Data source linking

Data sources are linked to model objects, establishing the connection between physical reality and the digital representation.

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Access permissions

User roles and access permissions are defined — management, operators, public, partners — each seeing only what they are authorised to see.

The no-code development environment means your domain experts — engineers, operations managers, city planners — can build and modify the model themselves. No software development team required. The twin is yours: you own the copyright and manage it independently.


03 — Analyse

AI monitors every process in real time — automatically.

Once the digital twin is live and connected, our multi-engine AI system runs continuously — processing every data stream, evaluating every object, and maintaining a real-time picture of your entire operation without any manual monitoring required.

What the analytical engine does:

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Real-time KPI processing

Every incoming data stream is transformed into KPI time-series. Values are calculated, aggregated across the system hierarchy, and updated continuously — from individual sensors up to the top-level system health score.

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Sustainability scoring

Each object and process in the digital twin receives an ongoing sustainability status — Excellent, Optimal, or Deficient — calculated automatically against your defined rules and targets. The whole system has a single composite health score at any moment.

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Anomaly detection

The system continuously compares live process patterns against established baselines. Statistical deviation, unexpected correlations, and early-stage anomalies are identified as they emerge — not after they escalate.

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Predictive analytics

Using machine learning models — including time-series forecasting, supervised classification, and deep learning pattern recognition — the platform projects the future trajectory of each process. Emerging risks are identified hours or days before they become operational problems.

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Root cause analysis

When an anomaly or non-compliance is detected, the system analyses contributing factors across connected processes — identifying correlations, cascading effects, and likely root causes automatically.

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Compliance monitoring

The model continuously checks every relevant KPI against embedded international and national standards. Non-compliance events are detected in real time, logged as auditable evidence, and flagged immediately.


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04 — Act

Receive alerts and recommendations before problems escalate.

The final step is where analysis becomes action. The platform does not produce data for analysts to interpret — it delivers conclusions, to the right people, at the right time, with recommended actions already attached.

The result is an operation that no longer relies on people watching screens or reading reports to know what is happening. The system watches, understands, and tells you — continuously, automatically, and before it is too late.


Ready to see it in action?

Experience the platform live.

Explore a live demonstration of the Pharos Navigator platform or contact our team to discuss your specific use case and deployment requirements.