Equipment deviations
Analyse temperatures, loads, and operating modes to help operators notice unusual behaviour and decide what to check first.
- What the pilot measures
- Time from a deviation to the team’s response, and the share of false alerts.
Industrial IoT · AI · Building OS
Infrastructure
management platform
Connect sensor, meter, and equipment data with monitoring and control. Help your team reduce operating costs, respond faster, and prevent downtime.
- One platform for buildings and distributed facilities
- Automated scenarios and accountable team actions
- 2027 AI direction: validate value with real facility data
5000+connected devices
10+years of engineering practice
24/7operational visibility
Works with your infrastructure
MQTTModbusBACnetONVIFREST APIVendor-independent
Context
IoT starts with devices. Value emerges through system management.
Sensors, controllers, meters, and local systems remain fragmented without one interaction model. They generate data but do not create coherent control.
AZIOT turns isolated nodes into an operational system for a building, facility, or distributed network.
40%of EU energy consumption comes from buildingsEuropean Commission
up to 30%of energy in commercial buildings is wasted by inefficient operationENERGY STAR
~80%of a building’s lifetime cost is operation, not constructionLifecycle studies
Solution
One platform instead of fragmented IoT tools
AZIOT connects equipment and data with AI analysis, rules, and operator actions in one controlled architecture.
Explore the architecture →Development direction · 2027
AI for everyday facility operations
In 2027, we plan to develop AZIOT around practical AI scenarios: from facility data analysis to operator recommendations. We will validate each scenario with real facility data in a pilot.
Planned directions. Feature availability, data requirements, and pilot scope are agreed for each facility.
Unusual resource consumption
Look for unusual electricity, water, or heating use in the context of operating schedules, weather, and facility occupancy.
- What the pilot measures
- Changes in consumption and costs under comparable operating conditions.
Recurring faults
Compare event history, equipment operating modes, and service records to investigate possible causes of recurring failures.
- What the pilot measures
- Diagnostic time, recurring incidents, and downtime duration.
Operator recommendations
Prepare a recommendation with event context and supporting data. An authorised employee reviews it and approves the next action.
- What the pilot measures
- Time spent handling an event and the share of recommendations useful for completing the task.
Intecracy Group’s 2027 strategy (Ukrainian) ↗Anton Marrero · 4 November 2026
Interactive Model
How AZIOT unifies engineering subsystems
Toggle groups directly or use the arrows to step through the model. Every node reports to one core — and one rule can move several subsystems at once.
Subsystems
15/ 15
active nodes in the model
Node inventory↕ scroll
Level 35
- Temperature / CO₂ SensorZigbee
- Lighting circuitDALI
- HVACModbus
- IP CameraONVIF
- Leak SensorModbus
Level 25
- Media HubHDMI CEC
- Temperature / HumidityZigbee
- Access ControlWiegand
- Energy MeterModbus
- LightingKNX
Level 15
- Turnstile2N
- Video IntercomSIP
- Electric PowerModbus
- Water SupplyM-Bus
- Fire AlarmRS-485
One AZIOT platform15 nodes4 subsystems1 control model
Modelled outcomes
From an operational problem to a measurable target
The percentages below are modelled targets, not verified deployment results. We agree on a target for your facility before the pilot.
01
30%lower utility costs for common areas
Residential complex: common-area management
Lighting, ventilation, and heating followed fixed schedules regardless of occupancy and weather.
Explore scenario ↗02
22%less energy used for apartment climate
Apartment: climate without overheating or manual tuning
Underfloor heating, air conditioning, and radiators competed with each other, requiring constant manual adjustments.
Explore scenario ↗03
24%energy savings across HVAC and lighting
Shopping mall: engineering systems driven by actual footfall
HVAC and lighting ran at the same output during peak and off-peak hours while operators used separate interfaces.
Explore scenario ↗Knowledge journal
IoT decisions with engineering context
Architecture, operational scenarios, protocols, and lessons connected to the AZIOT knowledge base.
Telemetry buffering on IoT gateways during connectivity loss
A practical matrix for selecting what an IoT gateway stores, evicts, and retransmits after a connection loss, considering MQTT 5.0 and Sparkplug B standards.
7 min
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IQusion IT Organized a Final Seminar on AI Governance and RAG
On October 19, 2026, LLC IQUSION IT held a final training seminar for its clients as part of the IQusion Days cycle – “AI Governance and RAG: Enhancing…
5 min
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IQusion presented updated HR systems with artificial intelligence technologies
On October 16, 2026, during the IQusion Days event, LLC IQUSION IT demonstrated updated human resource management information systems for businesses and…
4 min
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How we start
Three steps from audit to a managed network
Before starting, agree on how to measure success and which results justify a wider rollout.
Architecture session
Choose a task and check data and integrations. Agree on the baseline, target, budget, and responsibilities.
Pilot on one site
Validate the scenario with real data. Measure impact, false alerts, team effort, and total operating cost.
Rollout and support
Roll out scenarios with demonstrated value. Train the team and agree on support and a development plan.