Learn how AI is necessary to provide the deep observability and visibility into network and application performance for a exceptional user experience and zero outage branch.
Discover how enterprises are preparing their networks for AI. EMA’s research reveals critical insights on SD-WAN, SASE, security, and observability.
This blog shows how bringing LLM-powered automation into policy management helps security and networking teams build, audit, and optimize network policies more efficiently. It integrates into existing workflows, offering real-time access to current configurations and intelligent policy insights — all without requiring teams to switch tools.
The proliferation of AI and machine learning workloads has accelerated the generation and utilization of unstructured data—including emails, source code, collaboration files, logs, recordings, and internal documentation. Unlike structured data, which resides in databases, unstructured data spreads across cloud drives, SaaS applications, endpoints, and unmanaged collaboration tools.
As organizations increasingly embrace AI-powered coding tools to accelerate development and reduce engineering overhead, a new threat is emerging at the intersection of generative AI and open-source software (OSS): slopsquatting.
Secure your enterprise with AI-powered Versa SASE that boosts threat detection and response with real-time analytics, behavioral insights, and intelligent security automation for today’s digital landscape.
This blog summarizes the key takeaways from the report to help IT and network leaders understand the challenges ahead and where to focus as they modernize their infrastructure. It’s meant to help IT and network teams cut through the noise, pinpoint where their current approach may fall short, and prioritize the areas that will have the biggest impact on performance, security, and scalability.
Discover how agentic AI enhances threat detection, network optimization, Zero Trust security, and policy management. Learn how VersaAI Labs is driving AI-powered security innovation.
Shadow AI is exposing businesses to security risks and data leaks. Learn how to secure Generative AI usage with governance, AI firewalls, and compliance controls.
OWASP Top 10 for Large Language Model (LLM) Applications, highlighting critical security vulnerabilities such as prompt injection, data poisoning, and system prompt leakage. It emphasizes the need for proactive security measures, including Zero Trust principles, access controls, and continuous monitoring to protect AI-driven applications from emerging threats.
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