Spot anomalies earlier
The model helps identify unusual patterns in large volumes of data.
Anomaly detection
Spot anomalies in data and processes before they have an unseen impact.
Anomalies are not always easy to spot in large volumes of data. As a result, errors or disruptions can persist for some time. Anomaly detection identifies patterns that differ from what historical data would lead you to expect.
From an isolated possibility to a practical application
An application only becomes meaningful when it fits a specific task and the information available for that task.
An anomaly is a signal that needs further investigation. That is why we define in advance what the solution should and should not do, how the outcome will be checked and who remains responsible.
What it delivers
Prioritise investigations
Staff can focus on signals that need closer assessment.
Keep assessing performance
Monitoring shows how often signals prove useful or unnecessary.
Our approach
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Define the risk
We determine which anomalous behaviour matters and what a signal means.
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Examine the data
We analyse historical examples and data quality.
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Develop the model and set thresholds
We set up alerts with attention to unnecessary notifications.
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Validate with experts
Specialists assess signals and missed cases.
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Monitor
We track performance and changing patterns after the system goes live.
Aligned with your organisation
This service is relevant for organisations with data flows or operational processes. The exact setup depends on the process, the available data and the risks associated with the application.
We therefore start with a clearly defined application and only expand it once the initial setup works in practice.
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Frequently asked questions
This service addresses the following challenge: anomaly detection identifies patterns that differ from what historical data would lead you to expect. How it works in practice depends on the process and the data available.
The service can be relevant to organisations with data streams or operational processes. A clear need and usable information matter more than the size of the organisation.
That depends on the intended application. We start with the question you need to answer, then determine which data or sources are necessary and suitable.
No. For fixed, predictable tasks, standard automation may be enough. We choose the simplest approach that addresses the challenge and add complexity only when needed.
We define the scope of the application, check the results with users and put appropriate controls in place. Once it is in use, we monitor how it works and adjust the solution when the data, its use or the context changes.
Discover what anomaly detection could mean for your organisation
Want to explore where it makes sense to start with anomaly detection? Together, we’ll assess the challenge, the available information and the prerequisites.