Data Analytics for Decision Making

Transform sensor, process, and operational data into data-driven decisions that keep your operations running.

Turn industrial data into operational insight

Every industrial system generates massive amounts of data, but without the right analytics, much of its value remains untapped.

Wapice’s data analytics services help organisations turn complex, high-volume industrial data into actionable insight and foresight that reduce downtime, improve efficiency, and support better operational decisions.

We combine IoT connectivity, advanced analytics, and machine learning to build solutions that perform under real industrial conditions. Whether your goal is to predict equipment failures, detect subtle process anomalies, or forecast energy and resource consumption, we design and develop analytics around your assets, data, and operations.

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Common challenges we help solve

Sensor and process data is continuously collected, but identifying what actually requires attention can be difficult.

Traditional monitoring often reacts only after predefined thresholds are exceeded or equipment performance has already deteriorated.

Fixed maintenance intervals can lead to unnecessary work while still failing to prevent unexpected breakdowns.

Complex systems may involve hundreds of interacting variables, making emerging trends and abnormalities difficult to recognise manually.

From monitoring what happened to understanding what happens next

The key driver of insight

Data analytics enables organisations to move beyond traditional dashboards and reporting towards more predictive and automated decision-making.

By analysing sensor, process and operational data continuously, analytics can reveal developing equipment problems, unusual system behaviour and changing operational conditions before they become costly disruptions.

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Typical applications include:

Predictive maintenance and asset health monitoring
Anomaly and deviation detection
Energy and resource consumption forecasting
Process performance analysis and optimisation
Automated operational alerts and decision support

technician working on equipment

Predictive Maintenance

industrial digital twin

Predict failures before they disrupt operations

Unplanned downtime is one of the biggest cost drivers in industrial operations. Predictive maintenance shifts maintenance from reactive or calendar-based routines towards data-driven, condition-based decisions.

By analysing the actual behaviour and condition of equipment, developing problems can be identified early enough for maintenance to be planned before a failure interrupts operations.

We have delivered predictive maintenance solutions across manufacturing, energy and logistics environments using data such as:

Vibration and acoustic signals
Temperature and thermal measurements
Electrical and power quality data
Process and operational parameters

Analytics can be integrated directly into operational workflows using platforms such as IoT-TICKET, enabling continuous monitoring, automated alerts and clear visualisation of asset health.

Key outcomes include:

Reduced unplanned downtime through early failure detection
Extended asset lifetime through optimised maintenance scheduling
Lower maintenance costs by replacing time‑based routines with condition‑based strategies
Continuous visibility using real‑time dashboards and alerts

Anomaly Detection

Anomaly Detection in the Data Center

Detect the Unexpected

Not all problems announce themselves. Anomaly detection algorithms learn the normal behaviour patterns of your systems and flag deviations that may indicate developing faults, security issues, or process inefficiencies.

Wapice develops anomaly detection solutions for multiple types of industrial data, including:

Time-series sensor data
Multi-variable process data
Log files
Text data
Audio signals

Anomaly detection gives operations teams an early indication of changes that conventional threshold-based monitoring could miss.

Typical application areas include:

Equipment and system health monitoring
Log file patterns and irregularities
Detection of unusual patterns in sensor data

Make analytics part of everyday operations

The value of analytics does not come from the algorithm alone. It comes from choosing the right way to turn data into operational value. Depending on your needs, we can take either a tailored solution approach or build on our ready-made IoT-TICKET platform.

Tailored analytics solutions

Designed around your existing systems, data sources and operational processes.

A tailored solution is a good fit when the use case requires specialised analytics, unique integrations, specific user interfaces or close adaptation to an existing architecture.

Best suited for:

Complex or highly specialised use cases
Existing environments with specific integration requirements
Custom analytics models and workflows
Maximum flexibility in architecture and implementation

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IoT-TICKET platform

A ready-made IoT and analytics platform for connecting assets, processing data and bringing analytics into everyday operations.

IoT-TICKET provides a faster path from data collection to dashboards, alerts and operational insights, while still allowing the solution to be configured around the application and business need.

Best suited for:

Faster deployment and time to value
End-to-end IoT and analytics solutions
Continuous monitoring, dashboards and alerts
Scalable solutions across multiple assets and data sources

Key benefits of building AI capabilities with a partner:

Move faster from AI opportunity to concrete action.
Focus on the use cases that are worth prioritising.
Avoid disconnected pilots and costly false starts.
Build AI solutions that are ready for real use, not just proof of concept.
Strengthen internal capability through training, collaboration and shared ways of working.
Create a stronger foundation for long-term AI development and governance.

How we work

We begin every project with a collaborative phase to understand your data, processes, and objectives. From there, we move rapidly to proof of concept and after validation, to scalable implementation.

Team collaboration

1) From the challenge to use case

We begin by understanding your goals, data, processes and current readiness. This can start with a focused workshop, maturity assessment or use-case discovery session.

Validation

2) Validate what is worth building

Together, we prioritise use cases, assess feasibility and define a practical roadmap. When needed, we build a proof of concept to validate the idea with real data.

Implementation

3) Build for real use

Once the direction is clear, we design and implement the solution for production use — including integrations, deployment, governance and continuous development.

These are examples of ways how we usually start working with clients. Feel free to tell how you would like to start!

Put your industrial data to work

Whether you are exploring your first analytics use case or looking to bring advanced analytics into existing industrial systems, we can help identify the right approach and turn your data into practical operational value.

Let’s discuss your data analytics needs.

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