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Predictive Analytics & AI/ML
Predictive analytics & machine learning for your operational data
Months of sensor data hold the patterns behind breakdowns, waste, and demand. INCLUDE's predictive analytics & machine learning service builds models that detect anomalies and forecast trends from your operational data, then surfaces them as early warnings your team can act on.
Trusted by national & multinational companies
You have the data, but it is not working for you yet
Failures show up only after the machine stops
Maintenance still waits for breakdowns or follows a fixed schedule, not the real condition of the machine.
Data piles up unanalysed
Sensors and logsheets have run for years, yet nobody turns them into decisions.
Alarm thresholds are too rigid
Fixed limits raise false alarms in one condition and fire too late in another.
Planning still runs on guesswork
Energy, material, and production needs are planned from experience, not from patterns in the data.
What our predictive analytics & machine learning service covers
Data audit & preparation
We check the completeness and quality of historical data, then clean and structure it for modelling.
Anomaly detection
Models learn the normal pattern of each machine or process and flag it when behaviour drifts.
Predictive maintenance
Service predictions from vibration, temperature, current, and running hours, before failure happens.
Forecasting
Forecasts of energy demand, output, or material use for sharper planning.
Models at the edge or in the cloud
Models run in the cloud, or on an edge device when decisions must be fast or connectivity is limited.
Wired into dashboards & alarms
Model output appears on the INCLUDE platform as scores, forecasts, and alarms, not as a separate report nobody opens.
More than a project vendor
One team, from devices to AI
Hardware, firmware, software, integration, and AI are handled by the same team. No finger-pointing between vendors.
Built on a platform that already runs
Device management, dashboards, alarms, and access control already exist on the INCLUDE platform, so your project does not start from zero.
Start with a single pilot
Prove the value at one site or one line first, then scale once the results are visible.
Four steps from first call to live
Define the business question
We start from the decision you want to improve, such as when a machine needs service, not from an algorithm.
Assess the data
We review the data you have. If it falls short, we help add sensors or improve how it is recorded.
Build & validate the model
The model is trained and tested on your historical data, and the results are reviewed with your operations team.
Run & monitor
The model runs on the INCLUDE platform, its accuracy is tracked, and it is retrained when operating conditions change.
Connected to our products and solutions
Frequently asked questions
How much data does a model need?
It depends on the use case. Anomaly detection can start from normal operating data, while failure prediction needs a history of failures. We assess whether your data is enough before promising any result.
We don't have sensors yet. Where do we start?
Start by collecting data. Our team can install sensors and gateways first, and the model is built once there is enough data.
Can we trust what the AI model says?
Every model is tested on your historical data and the test results are shared with your team. Once live, the model is monitored and retrained if its accuracy drops.
How is this different from InAsset?
InAsset is a ready-made solution for machine service prediction with vibration limits based on ISO 10816. This service covers more specific cases, such as production processes, product quality, or forecasting that needs a bespoke model.
Explore other INCLUDE services
Let's talk about your Predictive Analytics & AI/ML needs
Tell us the problem. Our engineers will reply with a realistic first step, free and with no obligation.