Intelligent Maintenance & Operations
Deploy AI-powered workflow copilots that transform how your facilities and maintenance teams operate. From intelligent work order triage and auto-routing to predictive maintenance insights and automated reporting, move from reactive firefighting to proactive operations management.
The Maintenance Operations Challenge
Facilities and property maintenance teams across Australia operate in a constant state of reaction. Without intelligent systems to triage, prioritise, and route work orders, teams waste time on low-value tasks while critical issues go unaddressed.
Reactive Maintenance Culture
Most property and facilities teams operate in a perpetual cycle of reaction — waiting for things to break before addressing them. This reactive approach is fundamentally more expensive and disruptive than proactive maintenance. Emergency repairs cost 3-5 times more than planned maintenance, and unplanned downtime impacts tenant satisfaction, productivity, and building value. Without data-driven insights, teams cannot anticipate failures, plan preventative interventions, or allocate resources efficiently. The result is a constant state of firefighting that burns out staff and erodes building quality over time.
Manual Triage and Routing
When a work order arrives, someone — often a facilities coordinator or building manager — must manually read the request, assess its priority, determine the right trade or contractor, check availability, and assign the job. This manual triage process is slow, inconsistent, and heavily dependent on individual knowledge. When that person is on leave, sick, or overwhelmed with volume, the entire maintenance pipeline stalls. A single misrouted work order can delay resolution by days and trigger a cascade of complaints and escalations.
No Data-Driven Prioritisation
Without intelligent prioritisation, all work orders are treated as roughly equal — or worse, priority is determined by who shouts the loudest. A minor cosmetic issue reported by an executive tenant might get faster attention than a safety-critical HVAC failure in a server room. Data-driven prioritisation considers factors like safety risk, tenant impact, asset criticality, SLA requirements, and historical patterns to ensure the most important issues are addressed first. Without it, your team is making critical decisions based on gut feel rather than evidence.
Slow Resolution Times
From the moment a tenant reports an issue to the moment it is resolved, the average maintenance request passes through multiple handoffs, approval steps, and communication gaps. Each handoff introduces delay, potential miscommunication, and the risk of the request falling through the cracks entirely. In many portfolios, the average time from report to resolution for a non-urgent work order exceeds five business days — far longer than tenants expect. Slow resolution times directly impact tenant satisfaction scores, retention rates, and ultimately portfolio value.
How It Works
Our AI maintenance operations platform integrates with your existing systems and processes. No rip-and-replace — we enhance what you already have with an intelligent layer that learns and improves over time.
Integrate With Existing CMMS & Work Order Systems
We connect seamlessly with your existing CMMS, work order platforms, and building management systems — whether that is MEX, Archibus, FMI Works, Service Manager, Urbanise, or a custom solution. Our integration layer pulls in work order data, asset registers, contractor databases, and historical maintenance records without disrupting your current workflows or requiring data migration.
AI Triage and Auto-Routing
As work orders arrive, our AI reads and understands the request, automatically categorises it by trade, urgency, and asset type, then routes it to the right team or contractor based on skills, availability, location, and SLA requirements. The AI handles the entire triage process in seconds — including requesting additional information from the reporter when the initial request lacks detail.
Predictive Insights and Reporting
Beyond reactive triage, our AI analyses historical maintenance patterns to predict future failures, identify recurring issues, and recommend preventative actions. It generates automated reports on KPIs like mean time to resolution, first-time fix rates, contractor performance, and cost per work order — giving you the data you need to drive continuous improvement.
Continuous Learning and Optimisation
The AI learns from every work order, resolution, and outcome. It refines its triage accuracy, improves its routing decisions, and sharpens its predictive models over time. Regular feedback loops with your team ensure the AI stays aligned with operational priorities and evolving portfolio needs.
Key Features & Capabilities
Purpose-built for Australian property and facilities management, our AI maintenance platform combines workflow automation with predictive intelligence.
Intelligent Work Order Triage
AI reads, categorises, and prioritises incoming work orders in seconds. Understands natural language descriptions and automatically extracts key details like location, asset, urgency, and trade requirements.
Automated Contractor Routing
Match work orders to the right contractor based on trade specialisation, availability, proximity, performance history, and SLA requirements. Reduce assignment delays from hours to seconds.
Predictive Maintenance Insights
Analyse historical patterns to predict equipment failures before they occur. Identify assets approaching end-of-life, recurring fault patterns, and seasonal maintenance trends.
Automated Reporting
Generate comprehensive maintenance reports automatically — KPI dashboards, contractor scorecards, asset condition reports, and budget tracking. No more manual spreadsheet consolidation.
SLA Monitoring & Alerts
Track SLA compliance in real-time across your portfolio. Receive proactive alerts when work orders are at risk of breaching response or resolution timeframes.
Quality Assurance
AI-powered quality checks on work order completions. Verify that resolutions are properly documented, photos are attached, and follow-up actions are captured before closing.
Example Use Cases
AI-powered maintenance operations are delivering measurable results across diverse property types and portfolio sizes. Here are three scenarios where our technology creates transformative impact.
University Campus FM Operations
A major Australian university manages over 200 buildings across multiple campuses, processing thousands of maintenance requests monthly from students, staff, and faculty. Their AI maintenance copilot triages incoming requests automatically, routing urgent safety issues to on-call teams within minutes while batching non-urgent work orders for efficient scheduling. The system identifies recurring issues by building and floor, enabling targeted preventative maintenance programs that reduce reactive work orders by 40% within the first year. Predictive analytics flag ageing HVAC systems and plumbing infrastructure before catastrophic failures occur, protecting both occupant safety and university budgets.
Learn about Facilities Management AICommercial Office Portfolio Maintenance
A commercial property manager overseeing a portfolio of premium office towers deploys AI maintenance operations to standardise service delivery across all buildings. The AI enforces consistent triage protocols, ensures contractor compliance with building-specific requirements, and tracks SLA performance across the portfolio in real-time. Automated monthly reporting replaces hours of manual spreadsheet work, while predictive insights inform capital expenditure planning by identifying assets that are approaching replacement thresholds. The result is lower maintenance costs, higher tenant satisfaction, and better-informed asset management decisions.
Learn about Commercial Real Estate AIHospital Facilities Management
A hospital network uses AI maintenance operations to manage critical infrastructure across multiple sites. The system understands the heightened urgency of healthcare environments — a broken air conditioning unit in a server room or a malfunctioning door lock in a secure ward requires immediate escalation. The AI triages work orders with clinical context awareness, automatically escalates safety-critical issues, and ensures compliance with healthcare facility standards. Predictive maintenance of essential plant and equipment — including generators, medical gas systems, and sterilisation units — helps maintain accreditation and patient safety standards.
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Ready to Modernise Your Maintenance Operations?
Start with a Discovery Sprint to identify the highest-value AI use case for your maintenance and operations teams. In just 2-3 weeks, you will have a working prototype and a clear implementation roadmap.
Book a Discovery Sprint