Anomaly Detection

Fraud Detection

Veltris Insight can help build and train ML models to identify potential fraudulent activities faster, so you can avoid any online payment transactions before processing payments and fulfilling orders. The framework can also customize the models to cater to your own dataset, ensuring higher accuracy when compared to one-size-fits-all ML solutions.

Network Anomaly Detection

Veltris Insight enables detection and classification of anomalies in a network by building ML models that can continuously monitor the events in computer systems and networks by processing large volumes of the data generated by these sources. Using a deep packet inspection that combines the functionality of an intrusion detection system (IDS) and an intrusion prevention system (IPS), these models can detect network anomalies and attacks, while still ensuring data security.

IOT Signals & Data From Sensors

Veltris Insight ML models can detect unusual and erroneous readings to flag systems that are prone to failure, malfunction, rapid attrition, malicious attacks, theft, and tampering by processing big volumes of the data generated by IoT sensors. With this framework, we have built and compared the performances of several ML models to predict the anomalous behavior of IoT systems accurately. The ML algorithms primarily used are Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), etc.

Monitoring And Logging

Veltris Insight also provides for dashboards to track efficiency, create predictive maintenance plans, and remotely monitor the real-time status of all systems.

Anomaly Detection

Leverage AI To Foresee Problems Before They Occur

Improve Your Business By Detecting Anomalies in Your Data

Fraud Detection

Network Anomaly Detection

IOT Signals & Data From Sensors

Monitoring And Logging