
Best-in-class, Fraud.Net offers an AI-driven platform that empowers enterprises to combat fraud, streamline compliance, and manage risk at scale—all in real-time. Our cutting-edge technology detects threats before they impact your operations, providing highly accurate risk scoring that adapts to evolving fraud patterns through billions of analyzed transactions.
Our unified platform delivers complete protection through three proprietary capabilities: instant AI-powered risk scoring, continuous monitoring for proactive threat detection, and precision fraud prevention across payment types and channels. Additionally, Fraud.Net centralizes your fraud and risk management strategy while delivering advanced analytics that provide unmatched visibility and significantly reduce false positives and operational inefficiencies.
Trusted by payments companies, financial services, fintech, and commerce leaders worldwide, Fraud.Net tracks over a billion identities and protects against 600+ fraud methodologies, helping clients reduce fraud by 80% and false positives by 97%. Our no-code/low-code architecture ensures customizable workflows that scale with your business, and our Data Hub of dozens of 3rd party data integrations and Global Anti-Fraud Network ensures unparalleled accuracy.
Fraud is complex, but prevention shouldn't be. With FraudNet, you can build resilience today for tomorrow's opportunities. Request a demo today.
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Log360 is a comprehensive security information and event management (SIEM) solution designed to address threats across on-premises, cloud, and hybrid environments. Additionally, it assists organizations in maintaining compliance with various regulations like PCI DSS, HIPAA, and GDPR. This adaptable solution can be tailored to fit specific organizational needs, ensuring the protection of sensitive information.
With Log360, users have the ability to monitor and audit a wide range of activities across their Active Directory, network devices, employee workstations, file servers, databases, Microsoft 365, and various cloud services. The system effectively correlates log data from multiple sources to identify intricate attack patterns and persistent threats. It includes advanced behavioral analytics powered by machine learning, which identifies anomalies in user and entity behavior while providing associated risk scores. More than 1000 pre-defined, actionable reports present security analytics in a clear manner, facilitating informed decision-making. Moreover, log forensics can be conducted to delve deeper into the origins of security issues, enabling a thorough understanding of the challenges faced. The integrated incident management system further enhances the solution by automating remediation responses through smart workflows and seamless integration with widely used ticketing systems. This holistic approach ensures that organizations can respond to security incidents swiftly and effectively.
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Zilliz Cloud
While working with structured data is relatively straightforward, a significant majority—over 80%—of data generated today is unstructured, necessitating a different methodology. Machine learning plays a crucial role by transforming unstructured data into high-dimensional numerical vectors, which facilitates the discovery of underlying patterns and relationships within that data. However, conventional databases are not designed to handle vectors or embeddings, falling short in addressing the scalability and performance demands posed by unstructured data.
Zilliz Cloud is a cutting-edge, cloud-native vector database that efficiently stores, indexes, and searches through billions of embedding vectors, enabling sophisticated enterprise-level applications like similarity search, recommendation systems, and anomaly detection.
Built upon the widely-used open-source vector database Milvus, Zilliz Cloud seamlessly integrates with vectorizers from notable providers such as OpenAI, Cohere, and HuggingFace, among others. This dedicated platform is specifically engineered to tackle the complexities of managing vast numbers of embeddings, simplifying the process of developing scalable applications that can meet the needs of modern data challenges. Moreover, Zilliz Cloud not only enhances performance but also empowers organizations to harness the full potential of their unstructured data like never before.
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VictoriaMetrics Anomaly Detection
VictoriaMetrics Anomaly Detection is a continuous monitoring service that analyzes data within VictoriaMetrics to identify real-time unexpected variations in data patterns. This innovative solution employs customizable machine learning models to effectively pinpoint anomalies. As a vital component of our Enterprise offering, VictoriaMetrics Anomaly Detection serves as an essential resource for navigating the intricacies of system monitoring in an ever-evolving landscape. It significantly aids Site Reliability Engineers (SREs), DevOps professionals, and other teams by automating the intricate process of detecting unusual behavior in time series data. Unlike traditional threshold-based alerting systems, it leverages machine learning techniques to uncover anomalies, thereby reducing the occurrence of false positives and alleviating alert fatigue. The implementation of unified anomaly scores and streamlined alerting processes enables teams to swiftly recognize and resolve potential issues, ultimately enhancing the reliability of their systems. By adopting this advanced anomaly detection service, organizations can ensure more proactive and efficient management of their data-driven operations.
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