AI & IoT overview

Intelligence Built Into Facility Operations

IntelliGrid does not put AI in a separate dashboard for someone to review when they have time. It runs inside the operational workflow, so intelligence arrives as a ranked queue, a proposed action and a pre-filled work order.

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The business problem

AI that lives outside the workflow gets ignored

A separate analytics tool produces insight that nobody has time to act on. Findings are reviewed weekly at best, the person reading them cannot assign work from where they are standing, and the recommendation arrives without the asset context needed to judge it.

Insight separated from the place work is assignedNo asset or maintenance context attached to a findingReview cadence slower than the rate of deteriorationRecommendations that cannot be actioned in one step

The IntelliGrid approach

Data, context, decision, workflow, learning

Signals are normalised against the asset and location model, so AI works on context rather than raw numbers. Output lands in the operational queue with a proposed action, and the outcome of that action feeds back into the next assessment.

Context established before inferenceOutput placed in the queue operators already useRecommended action convertible to work in one stepOutcomes recorded and fed back into the model

Capabilities

Where AI operates in IntelliGrid

Predictive intelligence

Risk scored per asset and ranked across the portfolio by operational impact.

Anomaly detection

Deviation from established baselines across telemetry, alarms and runtime.

Alarm correlation

Related events grouped into a single incident with one owner.

Request classification

Occupant requests categorised, located and matched to the likely asset.

Priority proposal

Impact and urgency assessed to propose the applicable priority and SLA.

Technician matching

Assignment proposed from skill, zone, availability and asset familiarity.

Facility copilot

Natural-language questions answered against your own operational data.

Optimisation recommendation

Suggested adjustments for energy, workforce and asset utilisation.

Workflow

How intelligence flows

Data Context AI Decision Workflow Learning

Business benefits

Intelligence delivered where work is assigned, not in a separate tool Fewer duplicate call-outs through event correlation Consistent prioritisation independent of who takes the call Maintenance effort concentrated on genuine risk Decisions supported by the asset’s own operating history

Connects with

IoT sensors BMS CCMS Energy meters Work order engine WhatsApp Contact centre

See integration architecture →

Frequently asked

Does the AI act without human approval?

Automation is configurable. Alarm-to-work-order conversion can run on rules you define, while predictive findings are presented as a reviewed queue with a recommended action. Approval thresholds are set per deployment.

Related modules

Predictive Intelligence

Risk scoring across the portfolio

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Anomaly Detection

Deviation from baselines

Open →

AI Copilot

Ask your facility data a question

Open →

IoT

The data AI operates on

Open →

See AI inside the operational workflow

We will show the risk queue, classification and recommended-action handoff using your equipment classes.

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