Ververica Use Cases

In today's hyper-connected digital landscape, businesses are increasingly turning to advanced technologies to understand and engage with their customers more effectively than ever before. 

Fraud detection is a significant challenge across various industries, particularly in finance, insurance, and e-commerce. It involves identifying fraudulent activities or transactions, often within vast amounts of data.

In the fast-paced world of ride-hailing and food delivery services, companies must continuously innovate to meet customer demand while maintaining profitability. 

Extract, Transform, Load (ETL) systems have traditionally been batch-oriented, creating multiple layers of data such as bronze, silver, and gold. However, this approach can lead to inefficiencies, redundant storage, and increased costs.

Security Information and Event Management (SIEM) systems are essential tools for monitoring, detecting, and responding to security threats across enterprise environments.

AI and machine learning (ML) have become integral to customer experiences, particularly through chatbots, predictive models, and real-time decision-making engines.

Mainframes are the backbone of many critical business operations. While reliable, these slow, batch-oriented systems also have high operational costs, limited agility, and struggle to support today's demand for real-time insights and actions.