Anomaly Detection

Artificial intelligence automatically detects
and prioritizes problems

anomaly detection

Risk ranking and anomaly detection

Conduct an audit to gain insight into the financial health of companies, to detect anomalies and assess future risks.

Anomaly detection of fraud

Detect fraud more efficiently whether it is in insurance, bill payments, fraudulent account creation, identification of abnormal transactions...

Anomaly detection of individuals

Detection of individuals with unusual behavior, intruders in the building...

predictive maintenance

Predictive Maintenance

Detect anomalies preventively, anticipate breakdowns, reduce unscheduled downtime and improve production quality.

Why do we need to detect anomalies ?

Anomaly detection is the process of identifying data that do not conform to a normal pattern. The goal of anomaly detection is to identify unusual differences in large data sets.

Nowadays, the detection of anomalies is even more important with ever larger data sets, it is even more important to analyze them to avoid any interpretation errors. The first step is to find the abnormal values and determine if it is a security threat. The objective is to understand the cause of the anomaly to find the solution.

It can be used for many reasons, including as a tool to minimize risk and to detect fraud that may be difficult to find. It can also be used to resolve and guide business decisions.the detection of anomalies

How does Datategy's solution improve anomaly detection ?

Anomaly detection is important because it provides a better understanding of changes in business performance. 

papAI advantages
to detect anomalies

  • Time series integration natively via REST API/MQTT listening
  • No-code operation for cleaning dedicated to time series
  • No-code module dedicated to time series anomaly detection with encapsulated models, and form-based parameterization in an ergonomic interface
Data visualization

Customer Story

SNCF: Use papAI to detect faulty equipment

The SNCF, French public transport operator, decided to improve the maintenance processes of freight cars, the company’s industrial management decided to deploy an artificial intelligence (AI) solution to detect the presence of asbestos. Today, SNCF maintenance agents visually analyze and detect defective rail equipment.

To assist maintenance workers, the SNCF has deployed Datategy’s solution, an artificial intelligence platform in SaaS mode. The main challenge of implementing this tool within the maintenance department is to support the agents in their diagnosis.

Sncf Maintenance
"Today, when the solution tells us that there is no asbestos on a car, we can trust it 100%! It has never been wrong. And when it reports the presence of asbestos, the error rate is less than 1%. This tool provides real comfort on a daily basis, allowing time, safety and productivity for our teams."
Patrick Munsch
Head of Wagon Maintenance & Engineering at SNCF Voyageurs

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