Category: Edge AI

AI-powered computer vision is revolutionizing safety in manufacturing by enabling real-time detection of hazardous situations. These advanced systems offer unparalleled vigilance, ensuring proper PPE usage and monitoring complex interactions between workers, machinery, and vehicles. As AI technology continues to evolve, these systems will become even more accurate and adaptable, identifying subtle signs of danger before accidents occur.

Category: Network Computing

A mid-sized construction company was having a tough time dealing with several cybersecurity challenges in spite of their existing security measures, one of these challenges was keeping up with the volume of security alerts generated by their security tools, not to mention the existing network security team and measures lacked the experience and expertise in dealing with the more sophisticated threats. They found Lanner while seeking for a robust hardware solution on which an AI-enhanced managed detection and response (MDR) service can be built for enabling advanced threat detection, continuous monitoring and real-time response capabilities.

Category: Edge AI

Ensuring the safety of students and staff in schools has become increasingly challenging. Despite the presence of surveillance cameras, the sheer volume of footage makes it impractical for staff to manually review all video to identify incidents or suspicious activities. Immediate threats like on-campus conflicts, vandalism, and unauthorized access require quick, effective responses.

Category: Telecommunication

Businesses today face significant challenges in enhancing customer experiences while having to minimize their total cost of ownership (TCO). Such challenges bring about the need for innovative solutions that not only ensure security but also improve service efficiency as traditional IT infrastructures often struggle to keep up with the demands of modern, customer-facing applications. These   requirements are driving a shift towards edge AI, where processing occurs closer to the data source, in real-time, with reduced latency and enhanced privacy.

Category: Network Computing

Nowadays, cybersecurity companies are increasingly turning to AI and machine learning to enhance malware detection, as traditional signature-based methods prove insufficient against evolving threats. The AI engine analyzes vast amounts of security data to identify trends, anomalies, and predict potential threats, enabling proactive measures. It establishes a baseline of normal behavior and monitors for deviations, facilitating early detection.

Category: SD-WAN

Business continuity is the ability to maintain core business functions without downtime during disruptive events. While it involves many components across all business functions, contingency planning for network infrastructure is of the upmost importance as having no functioning enterprise networks means no essential connectivities for business-critical services such as cloud storage, digital payment systems, CDPs, CRMs, SaaS applications, and VoIP.

Category: Transportation

Rail service providers are facing increasing cybersecurity risks within their wayside signaling and train control infrastructure. With thousands of rail-specific assets and applications distributed across a wide network, there is a pressing need for continuous threat detection and monitoring to ensure network integrity and passenger safety.

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