Industry Solutions
Built for the Industries That Can't Afford Downtime.
Digital Duo adapts to the operational realities of your industry — not the other way around. Three verticals, one platform, zero tolerance for unplanned failure.
Manufacturing & Industrial
From reactive maintenance to predictive operations.
Unplanned downtime in discrete and process manufacturing costs an average of $260,000 per hour. Digital Duo creates a live digital twin of every production asset — CNC machines, conveyors, compressors, robotic arms — and runs continuous AI inference to predict failures before they cascade into line stoppages.
Pain Points Addressed
Unplanned downtime
Reactive maintenance cycles mean failures are discovered after they've already stopped production
OEE blind spots
Operators lack real-time visibility into availability, performance, and quality losses across the line
Siloed asset data
SCADA, MES, and ERP systems hold disconnected data that no single team can act on holistically
Slow root-cause analysis
Post-incident investigations take days of manual log review — by which time the next failure is already forming
Use Cases
Predictive Maintenance
LSTM models trained on vibration, temperature, and current draw data predict bearing failures, motor degradation, and seal wear 48–96 hours in advance. Work orders are auto-generated in SAP PM or IBM Maximo before the failure window.
OEE Optimisation
The Duo Dashboard renders a live OEE breakdown — availability, performance, quality — per line, per cell, per shift. The AI layer identifies the top three loss contributors each day and prescribes targeted interventions.
Production Simulation
Before changing shift patterns, line speeds, or maintenance schedules, engineers run What-If simulations to project the impact on throughput, energy consumption, and MTBF — without touching the physical line.
Quality Anomaly Detection
Sensor fusion across process variables (temperature, pressure, feed rate) detects out-of-spec conditions in real time, triggering alerts before defective product reaches downstream stages.
Before / After Outcomes
Unplanned downtime
18%
4%
Mean time to repair
6.2 hrs
1.8 hrs
OEE score
61%
84%
Maintenance cost per unit
$4.20
$1.90
Native Integrations
Platform Modules Used
Challenge
A 1,200-person stamping plant was experiencing 22 unplanned stoppages per month across 48 press lines, costing an estimated €4.1M annually in lost production.
Result
After a 90-day Digital Duo pilot, unplanned stoppages dropped to 4 per month. The AI engine identified a systematic lubrication degradation pattern across 12 presses that had been invisible to the existing SCADA system.
Smart Buildings & Real Estate
Intelligent buildings that pay for themselves.
Commercial real estate accounts for 40% of global energy consumption. Digital Duo creates a living digital twin of every building system — HVAC, electrical, elevators, fire suppression, access control — enabling operators to cut energy waste, predict equipment failures, and meet ESG commitments with auditable data.
Pain Points Addressed
Energy waste
HVAC and lighting systems run on fixed schedules regardless of occupancy, weather, or real-time demand
Reactive FM
Facilities management teams respond to tenant complaints rather than predicting and preventing equipment failures
ESG reporting gaps
Sustainability teams lack granular, auditable energy and carbon data at the asset and floor level
Multi-site complexity
Portfolio operators managing dozens of buildings have no unified view of asset health or energy performance
Use Cases
HVAC Optimisation
The twin models thermal dynamics, occupancy patterns, and weather forecasts to run HVAC at minimum energy cost while maintaining comfort. Setpoints are adjusted autonomously every 15 minutes based on AI recommendations.
Predictive Equipment Maintenance
Chiller degradation, AHU bearing wear, and cooling tower fouling are detected 2–4 weeks before failure using vibration and performance trend analysis — eliminating emergency call-outs and tenant disruption.
ESG & Carbon Reporting
Digital Duo aggregates energy consumption, carbon intensity, and waste data at building, floor, and system level. Reports are auto-generated in GRESB, ENERGY STAR, and CRREM formats for compliance and investor disclosure.
Portfolio Command Centre
A single Duo Dashboard view across an entire real estate portfolio — health scores, energy rankings, active alerts, and maintenance backlogs — with drill-down to individual floor plans and asset schematics.
Before / After Outcomes
Energy consumption
Baseline
−31%
FM reactive call-outs
42/month
9/month
Chiller MTBF
14 months
26 months
ESG reporting time
3 weeks
4 hours
Native Integrations
Platform Modules Used
Challenge
A 14-building, 280,000 sqm commercial portfolio was spending SGD 8.2M annually on energy and facing increasing pressure from institutional investors to demonstrate Scope 1 and 2 emissions reductions.
Result
Digital Duo's HVAC optimisation and predictive maintenance modules delivered a 28% reduction in energy spend in the first year. The portfolio achieved GRESB 4-Star rating for the first time, directly cited in two investor ESG disclosures.
Supply Chain & Logistics
See every node. Predict every disruption.
Modern supply chains are networks of interdependent physical assets — warehouses, conveyor systems, sortation lines, cold storage, last-mile fleets. A single node failure cascades across the entire network. Digital Duo creates a real-time twin of your physical logistics infrastructure, predicting bottlenecks and equipment failures before they propagate.
Pain Points Addressed
Cascade failures
A single conveyor or sortation failure can halt an entire fulfilment centre, with knock-on effects across the network
Cold chain integrity
Temperature excursions in cold storage and refrigerated transport are detected too late to prevent spoilage or compliance breaches
Throughput variability
Seasonal demand spikes expose hidden capacity constraints that only become visible when SLAs are already breached
Fleet asset health
Last-mile vehicle fleets lack predictive maintenance, leading to on-route breakdowns and missed delivery windows
Use Cases
Fulfilment Centre Twin
Every conveyor belt, sorter, scanner, and dock door is modelled in the twin. The AI layer predicts jam events, motor failures, and throughput bottlenecks 4–12 hours ahead, enabling pre-emptive rerouting and maintenance scheduling.
Cold Chain Monitoring
Continuous temperature, humidity, and door-open event monitoring across cold rooms and refrigerated vehicles. Excursion predictions are issued before thresholds are breached, with automated alerts to compliance teams and logistics managers.
Network Capacity Simulation
Before peak season, logistics planners run What-If simulations modelling demand uplift scenarios against current asset capacity — identifying which nodes will fail first and what infrastructure investments deliver the highest throughput ROI.
Fleet Predictive Maintenance
Telematics data from last-mile vehicles feeds the twin engine. Engine health scores, brake wear predictions, and tyre degradation forecasts are surfaced to fleet managers 7–14 days before failure, eliminating on-route breakdowns.
Before / After Outcomes
Conveyor unplanned downtime
14 hrs/month
2.1 hrs/month
Cold chain excursions
23/quarter
2/quarter
Peak season SLA breach
8.4%
0.9%
Fleet on-route breakdowns
11/month
1/month
Native Integrations
Platform Modules Used
Challenge
A 3PL operating four fulfilment centres across the Benelux region was experiencing an average of 31 unplanned conveyor stoppages per month during peak season, causing 4,200 delayed shipments and €1.8M in SLA penalty payments.
Result
Digital Duo's fulfilment centre twin reduced unplanned stoppages to 3 per month within 60 days. The AI engine identified a systematic pattern of motor overheating on a specific conveyor model under high-humidity conditions — a failure mode that had never been documented.
Talk to a Solutions Engineer
Find Out What Digital Duo Can Do for Your Operation
Our solutions engineers have deep domain expertise in your vertical. Tell us about your operation and we'll map the platform to your specific assets, systems, and KPIs — no generic demo, no sales pitch.