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7 Key Benefits of AI-Powered SASE for Organizations

Today, remote work and cloud-based applications have become the norm, which means organizations are facing mounting challenges in managing and securing their networks. The rapid increase in data flow, reliance on cloud services, and the need for seamless connectivity from any location require a modern approach to networking and security. This is where AI-powered Secure Access Service Edge (SASE) comes into play.

AI-powered SASE is a groundbreaking network architecture that combines networking and security capabilities with artificial intelligence to create an intelligent, proactive, and adaptive framework. Unlike traditional network systems that struggle to meet the demands of today’s decentralized work environment, AI-powered SASE enables organizations to streamline operations, enhance security, and improve performance.

It integrates technologies like software-defined wide area networking (SD-WAN), secure web gateways (SWG), cloud access security brokers (CASB), and Zero Trust network access (ZTNA) under a unified, cloud-based solution. By harnessing the power of AI, it delivers capabilities such as autonomous management, predictive analytics, and real-time threat detection.

The increasing reliance on remote work has further highlighted the need for integrated, AI-driven solutions. Employees and contractors now access enterprise resources from diverse locations, creating a vast attack surface and raising the stakes for network security.

The shift to hybrid and fully remote work models also demands flexible and scalable solutions that cater to dynamic user requirements. Traditional security measures and on-premises infrastructure are no longer sufficient to safeguard sensitive data or ensure uninterrupted connectivity.

AI-powered SASE addresses these challenges by providing a comprehensive, future-ready solution. It bridges the gap between networking and security, leveraging artificial intelligence to make smarter decisions, predict potential issues, and offer real-time solutions. As organizations navigate the complexities of digital transformation, AI-powered SASE emerges as an indispensable tool for achieving operational efficiency, robust security, and exceptional user experiences.

What is SASE?

Secure Access Service Edge (SASE) is a transformative network and security framework designed for the digital-first era. Coined by Gartner in 2019, SASE represents the convergence of networking and security capabilities into a single, unified cloud-based service. This innovative architecture eliminates the need for traditional, hardware-based systems and offers organizations the flexibility and scalability they need to adapt to changing business environments.

Definition of SASE

SASE integrates various network and security functions into a cohesive framework, enabling secure access to resources regardless of location. Its cloud-native design ensures that users can connect directly to applications and data centers without relying on traditional data backhauls or cumbersome network appliances. SASE emphasizes the importance of Zero Trust principles, requiring strict identity verification and access controls to protect sensitive data.

Key Components of SASE

At its core, SASE combines four primary components to deliver its comprehensive capabilities:

  1. Software-Defined Wide Area Networking (SD-WAN): SD-WAN provides dynamic, application-aware routing across multiple network paths, optimizing connectivity and performance. It ensures efficient data flow between branch offices, cloud services, and end-users.
  2. Secure Web Gateway (SWG): SWG protects users from internet-based threats by filtering web traffic, blocking malicious websites, and enforcing corporate browsing policies.
  3. Cloud Access Security Broker (CASB): CASB enhances cloud security by monitoring and controlling access to cloud-based applications, ensuring compliance and preventing data leaks.
  4. Zero Trust Network Access (ZTNA): ZTNA enforces granular access controls based on user identity, device posture, and security policies, minimizing the risk of unauthorized access.

The Shift to Cloud-Based SASE Frameworks

Traditional network models were designed for on-premises environments, with a centralized data center serving as the hub for all traffic. This approach is ill-suited for today’s distributed workforces and cloud-heavy ecosystems. SASE shifts the focus to the cloud, enabling direct, secure connections between users and applications without unnecessary detours.

The migration to SASE frameworks is driven by several factors:

  • Remote Work: The rise of remote work has decentralized workforces, requiring secure and flexible connectivity options.
  • Cloud Adoption: Organizations increasingly rely on cloud-based services, necessitating a security framework that aligns with their cloud strategies.
  • Dynamic Threat Landscape: Cybersecurity threats are more sophisticated than ever, demanding integrated solutions that can adapt and respond in real-time.

By combining advanced networking with robust security measures, SASE provides a scalable, future-ready solution for organizations navigating digital transformation.

The Role of AI in SASE

Artificial intelligence plays a pivotal role in transforming SASE from a traditional framework into a dynamic, intelligent system capable of addressing modern networking and security challenges. AI introduces advanced capabilities such as autonomous management, predictive analytics, and real-time threat detection, making SASE a more effective and efficient solution for organizations.

AI’s Contribution to SASE Networking and Security

AI enhances SASE’s ability to manage complex network environments by automating routine tasks and analyzing vast amounts of data. Its key contributions include:

  • Data Aggregation: AI consolidates data from multiple sources, including network activity, user behavior, and threat intelligence. This centralized approach allows IT teams to gain a unified view of the system.
  • Threat Detection: By leveraging machine learning algorithms, AI can identify patterns and anomalies indicative of cyber threats, such as phishing attempts or unauthorized access.
  • Autonomous Management: AI enables SASE systems to make real-time decisions, such as rerouting traffic to avoid congestion or isolating compromised devices to contain security breaches.

Introduction to AIOps

AI Operations (AIOps) is a crucial component of AI-powered SASE. AIOps uses AI and machine learning to automate IT operations, providing capabilities such as:

  • Predictive Analytics: AIOps identifies potential issues before they escalate, enabling proactive remediation.
  • Anomaly Detection: It monitors network behavior for irregularities and flags potential risks.
  • Simplified Troubleshooting: AIOps reduces the mean time to resolution (MTTR) by streamlining diagnostics and providing actionable insights.

Through these enhancements, AI elevates SASE’s effectiveness, making it an indispensable tool for organizations seeking robust network management and security.

How AI-Powered SASE Works

AI-powered SASE integrates artificial intelligence into its architecture to optimize both networking and security functions. Its operation revolves around three key pillars: networking, security, and data management.

Networking: AI-Driven Resource Allocation

AI-powered SASE uses historical data and user behavior to predict network demands and allocate resources proactively. This approach minimizes latency, ensures optimal bandwidth utilization, and enhances the overall user experience.

Security: Proactive Threat Detection and Mitigation

AI’s role in security is central to SASE’s effectiveness. Machine learning algorithms analyze network traffic to detect anomalies and potential threats. When a threat is identified, the system can isolate it, preventing lateral movement and minimizing damage. Over time, the system learns from new threat patterns, continuously improving its defenses.

Centralized Data Management and Continuous Learning

AI-powered SASE collects and stores data from network and security events in a central data lake. This unified data repository supports AI algorithms in learning and adapting, enabling the system to evolve and remain effective in the face of emerging challenges.

By combining these elements, AI-powered SASE provides a proactive, intelligent, and adaptive framework that empowers organizations to secure their networks and enhance performance.

Key Benefits of AI-Powered SASE

The adoption of AI-powered Secure Access Service Edge (SASE) represents a significant evolution in networking and security strategies for modern organizations. By leveraging artificial intelligence, AI-powered SASE transcends the limitations of traditional approaches, delivering a range of benefits that enhance cybersecurity, streamline IT operations, and improve network performance. Below, we explore these benefits in detail.

1. Enhanced Cybersecurity

With sophisticated cyber threats and ever-evolving attack vectors, enhanced cybersecurity is arguably the most critical benefit of AI-powered Secure Access Service Edge (SASE). By integrating advanced artificial intelligence and machine learning capabilities, AI-powered SASE provides a proactive, adaptive, and robust approach to network security. Here’s a detailed exploration of how it achieves this.

1. Real-Time Threat Detection and Prevention

Traditional security systems often rely on static rules or reactive mechanisms, leaving networks vulnerable to zero-day threats or advanced persistent threats (APTs). AI-powered SASE, in contrast, operates in real time, detecting and mitigating threats as they emerge.

  • Behavioral Analysis: Machine learning algorithms analyze network behavior to detect anomalies indicative of malicious activity. For instance, if a device exhibits unusual data transfer patterns, AI can flag and investigate the activity in seconds.
  • Automated Responses: When a potential threat is identified, AI-powered SASE systems can automatically isolate compromised endpoints, block malicious traffic, or quarantine affected resources. This rapid response prevents threats from propagating across the network.
  • Dynamic Threat Updates: AI systems continuously learn from new attack patterns, adapting their defense mechanisms to counter emerging threats. This dynamic approach ensures the network’s security posture remains resilient in the face of evolving challenges.

2. Advanced Threat Intelligence with Machine Learning

AI-powered SASE employs machine learning models that process and analyze vast amounts of data, uncovering patterns and trends invisible to traditional security systems.

  • Threat Prediction: By examining historical data, AI can predict potential vulnerabilities and suggest preventative measures before an attack occurs. For instance, AI might identify a pattern of login attempts resembling a brute-force attack and implement stricter authentication protocols.
  • Phishing Detection: Machine learning excels at identifying phishing attempts by analyzing email metadata, webpage designs, and URL patterns. This ensures that employees and users are less likely to fall victim to deceptive schemes.
  • Customized Threat Profiles: Organizations often face unique security challenges based on their industry or operational scope. AI-powered SASE can create customized threat intelligence profiles, tailoring security measures to meet specific requirements.

3. Improved Phishing and DNS Threat Mitigation

Phishing remains one of the most common and effective cyberattacks. DNS threats, such as cache poisoning or tunneling, also pose significant risks. AI-powered SASE provides advanced mechanisms to combat these challenges.

  • Phishing Mitigation: AI tools analyze email content, URLs, and attachments for signs of phishing. By leveraging natural language processing (NLP) and image recognition, these tools can detect even the most convincing phishing attempts.
  • DNS Threat Detection: AI-powered systems monitor DNS traffic for anomalies that might indicate malicious activity. For example, an unusually high number of DNS queries to a suspicious domain could trigger an alert.
  • Continuous Learning: As attackers refine their techniques, AI-powered SASE systems update their models to recognize new strategies, ensuring sustained protection against phishing and DNS threats.

4. Comprehensive Network Protection

Unlike traditional security solutions that focus on specific components, AI-powered SASE provides end-to-end protection across the entire network.

  • Zero Trust Architecture: AI reinforces the Zero Trust model by continuously verifying the identity and behavior of users and devices. Suspicious activity triggers immediate action, ensuring only authorized access to resources.
  • Encrypted Traffic Inspection: Many cyberattacks hide within encrypted traffic, making detection challenging. AI-powered SASE can analyze encrypted data streams without compromising privacy, identifying threats hidden within SSL/TLS traffic.
  • Global Threat Intelligence Sharing: AI-powered SASE solutions often integrate with global threat intelligence networks. This allows organizations to benefit from insights into threats observed across other environments, improving their defensive capabilities.

5. Proactive Threat Mitigation

A key advantage of AI-powered SASE is its proactive approach to security. Rather than waiting for attacks to occur, these systems anticipate and neutralize threats before they can materialize.

  • Predictive Analytics: By analyzing trends and behaviors, AI-powered SASE predicts where vulnerabilities might appear, enabling organizations to address weaknesses proactively.
  • Automated Patching: AI can identify software or hardware vulnerabilities and recommend or implement patches, closing security gaps before attackers exploit them.
  • Continuous Monitoring: Around-the-clock monitoring ensures that threats are identified and addressed, regardless of when they occur.

6. Compliance and Industry Standards

Maintaining compliance with industry regulations and standards is a critical aspect of cybersecurity. AI-powered SASE simplifies this process through automated compliance checks and reporting.

  • Regulatory Adherence: AI ensures that security measures align with frameworks like GDPR, HIPAA, and PCI DSS. Automated monitoring verifies that policies and practices meet regulatory requirements.
  • Audit Readiness: With AI’s ability to generate detailed logs and reports, organizations can prepare for audits more efficiently, demonstrating their commitment to compliance.

Enhanced cybersecurity is at the heart of AI-powered SASE, providing organizations with the tools they need to defend against an increasingly complex threat landscape. Through real-time threat detection, advanced machine learning, and proactive mitigation strategies, AI-powered SASE transforms network security into a dynamic and adaptive system. By continuously learning, evolving, and integrating cutting-edge intelligence, AI-powered SASE ensures that organizations can operate confidently in a digital-first world.

2. Streamlined IT Administration: Simplifying Network Management with AI-Powered SASE

In the rapidly evolving landscape of enterprise IT, managing complex networks and ensuring seamless operations is a significant challenge. AI-powered SASE transforms IT administration by automating routine tasks, enhancing efficiency, and enabling proactive problem resolution. Let’s delve into how this integration provides streamlined IT administration.

1. Reduced Administrative Burden with Automation

One of the primary benefits of AI-powered SASE is its ability to automate mundane administrative tasks. Traditional IT environments require significant manual intervention to manage configurations, troubleshoot issues, and ensure network health. However, AI-powered SASE alleviates this burden through advanced automation.

  • Workflow Automation: Routine tasks such as user provisioning, policy enforcement, and system updates are automated, allowing IT teams to focus on strategic initiatives rather than repetitive tasks.
  • Self-Healing Networks: AI-powered systems continuously monitor network health, automatically resolving minor issues such as network congestion or service degradation without human intervention.
  • Customization and Efficiency: Automation also allows IT administrators to tailor workflows to meet specific business needs, ensuring that operations are both efficient and responsive.

2. Integration of AIOps for Faster Issue Resolution and Predictive Management

AIOps, the integration of AI with IT Operations, plays a pivotal role in enhancing IT administration. AIOps enables the automation of complex IT operations, providing real-time insights and predictive analytics for faster issue resolution.

  • Predictive Problem Management: AI-powered SASE uses historical data and current network behavior to predict potential issues, enabling proactive remediation. For example, if a certain application consistently causes high latency, AI can predict and address the problem before end-users experience disruption.
  • Real-time Monitoring: With AI’s ability to analyze vast amounts of data, AIOps delivers real-time insights into network performance. This allows IT teams to swiftly identify anomalies and take corrective actions, reducing Mean Time to Resolution (MTTR).
  • Simplified Issue Handling: Through integrated dashboards and automated responses, IT administrators can handle multiple issues simultaneously, ensuring a streamlined approach to problem resolution.

3. Centralized Management and Control

Managing dispersed networks across multiple locations is a challenging task. AI-powered SASE simplifies this by offering a centralized management system that integrates networking and security functions into a unified framework.

  • Unified Dashboard: IT administrators can access a single, comprehensive dashboard to monitor, manage, and secure the entire network from a centralized location. This centralization improves visibility and reduces the complexity associated with managing separate systems.
  • Policy Enforcement Across Locations: AI-powered SASE ensures that security policies are consistently applied across all branches, remote sites, and user devices, regardless of their geographical location.

4. Enhanced Proactive Security and Automation

Beyond traditional network management, AI-powered SASE proactively enhances security while streamlining administrative efforts.

  • Automated Threat Detection and Response: AI continuously monitors for security threats, enabling IT administrators to address potential risks before they materialize into full-scale attacks. Threat intelligence from AI-driven systems helps in making informed decisions for risk mitigation.
  • Incident Management Automation: AI-powered SASE reduces the manual effort required to manage incidents by automating the orchestration of incident responses, including isolating affected systems and initiating recovery processes.

5. Continuous Improvement Through Machine Learning

Machine learning is fundamental to the adaptive nature of AI-powered SASE. As networks evolve and new challenges emerge, AI refines its understanding of network behavior, ensuring continuous improvement in IT administration.

  • Continuous Training: AI models learn from every interaction, enhancing their capability to manage complex environments. This continuous feedback loop improves the accuracy of predictions and reduces false positives.
  • User Behavior Analytics: AI-driven analytics allow IT teams to understand user behavior and adapt administrative strategies to meet evolving business needs. This helps in reducing operational overhead while maintaining high levels of security and performance.

6. Cost Savings and Efficiency

Streamlining IT administration through AI-powered SASE not only improves productivity but also contributes to cost savings. By automating labor-intensive tasks, organizations can reallocate resources to higher-value activities.

  • Reduced Staffing Needs: Automation and AI-based management reduce the need for large IT teams, lowering operational expenses while maintaining service quality.
  • Improved Resource Utilization: AI-driven resource allocation ensures that network resources are optimized efficiently, reducing unnecessary expenditures and maximizing the return on IT investments.

AI-powered SASE revolutionizes IT administration by providing automation, centralized management, and predictive insights that drive efficiency and security. Through AIOps, IT teams can handle complex network environments with ease, minimizing administrative burdens and enabling proactive, data-driven decision-making. As a result, organizations can achieve streamlined operations, reduced downtime, and enhanced productivity in today’s digital-first landscape.

2. Streamlined IT Administration: Simplifying Network Management with AI-Powered SASE

Effective IT administration is the backbone of any organization’s technological infrastructure, especially in today’s fast-paced and increasingly complex networking environment. With the rise of cloud computing, remote workforces, and the growing need for agile, secure connectivity, traditional network management approaches are often too rigid, slow, and fragmented.

AI-powered SASE (Secure Access Service Edge) changes the game by streamlining IT administration, significantly reducing the manual workload for IT teams and enhancing operational efficiency. In this section, we will explore how AI-powered SASE facilitates streamlined IT administration through automation, AIOps, and intelligent decision-making.

1. Reduced Administrative Burden with Automation

A significant advantage of AI-powered SASE is its ability to automate many of the routine, time-consuming tasks traditionally handled by IT administrators. In conventional network environments, administrators spend a considerable amount of time configuring devices, applying policies, troubleshooting issues, and maintaining system performance. However, with AI, these processes are automated, freeing up valuable resources for more strategic and high-priority tasks.

Automated Network Configuration and Management

AI-powered SASE systems can automatically configure and manage network devices, ensuring that security policies and settings are consistently applied across the network, regardless of user location or network endpoint. This reduces the need for manual configuration, especially in distributed networks with multiple branches and remote employees. Automated configuration management also reduces the likelihood of human error, which can often lead to security vulnerabilities and network downtime.

Self-Healing Networks

AI-powered SASE platforms can autonomously identify and resolve minor network issues in real time, making networks more resilient. For example, if there is a performance degradation or a drop in connectivity, AI can automatically adjust traffic flows or re-route network traffic to alleviate congestion or failure points, minimizing the impact on end-users. This reduces the burden on IT teams, who would traditionally need to manually intervene to correct such issues.

Policy Automation

Another critical area where automation excels is in policy enforcement. Network security policies such as access control, bandwidth allocation, and threat protection need to be implemented across the network. AI-powered SASE can automate policy enforcement based on the organization’s security requirements, ensuring that each device, user, or service adheres to the same set of rules without manual intervention. This consistency is vital for maintaining a secure and efficient network environment.

2. Integration of AIOps for Faster Issue Resolution and Predictive Management

AIOps (Artificial Intelligence for IT Operations) is an integral part of AI-powered SASE, enabling faster issue resolution and proactive management of network infrastructure. AIOps tools leverage machine learning algorithms and data analytics to identify patterns, detect anomalies, and predict potential issues before they affect network performance or security.

This allows organizations to take a more proactive approach to IT management, reducing the time spent on firefighting issues and allowing IT teams to focus on strategic initiatives.

Proactive Issue Detection and Prediction

With AI-driven predictive analytics, AIOps within SASE platforms can identify emerging problems before they escalate. For instance, if a pattern of network latency or application slowness begins to emerge, AI can analyze historical data and network usage to predict when and where these issues will likely occur. IT administrators can then take preemptive actions to prevent service interruptions, avoiding costly downtime and improving user experience.

Root Cause Analysis

When issues do occur, AIOps can quickly pinpoint the root cause by analyzing data from across the network. Traditionally, resolving network issues requires significant time and effort, often involving trial and error and escalating to higher-level experts. AIOps automates this process by correlating data from various sources, such as logs, monitoring systems, and performance metrics, to pinpoint the exact source of the problem. This reduces Mean Time to Resolution (MTTR) and enables IT teams to address issues faster and more efficiently.

Automated Remediation

Once a potential issue is detected and its cause identified, AI-powered SASE can automate remediation actions, such as rerouting traffic, resetting devices, or applying patches. These automated responses reduce the administrative workload and enhance the speed of resolution, ensuring that network performance is not significantly impacted by minor incidents.

3. Centralized Management and Control

Managing modern network infrastructures—especially those involving hybrid cloud environments, remote workforces, and multiple branch locations—can be complex and fragmented. AI-powered SASE centralizes the management and control of networking and security tasks, providing IT administrators with a unified view of the entire system from a single dashboard. This centralization simplifies monitoring, troubleshooting, and decision-making, reducing the need for multiple systems and interfaces.

Unified Management Interface

With AI-powered SASE, IT administrators no longer need to manage disparate systems for networking, security, and operations. Instead, they can access a single interface that integrates various functions, such as SD-WAN (Software-Defined Wide Area Network), CASB (Cloud Access Security Broker), SWG (Secure Web Gateway), and ZTNA (Zero Trust Network Access). This unified approach improves efficiency by allowing administrators to monitor, configure, and secure the entire network from one platform, reducing complexity and eliminating the need for manual coordination between separate systems.

Real-Time Visibility

AI-driven dashboards provide real-time visibility into network performance, security threats, and user activity. IT administrators can quickly assess the health of the network, monitor traffic patterns, and detect security incidents without having to manually gather and analyze data from multiple sources. This instant access to network insights enables faster decision-making and a more agile response to changing conditions.

Policy Consistency Across Locations

In large, distributed organizations, ensuring that security policies are consistently applied across all locations and endpoints is often a challenge. AI-powered SASE addresses this by ensuring that security and access control policies are enforced across all branches, remote workers, and cloud applications, regardless of physical location. AI systems automatically adjust policies to meet the specific needs of users and devices, ensuring compliance and consistency without manual intervention.

4. Enhanced Proactive Security and Automation

AI-powered SASE is not just about streamlining IT administration—it also significantly improves network security by automating threat detection, prevention, and response. The traditional method of manually identifying and mitigating security threats can be slow and reactive, often resulting in missed vulnerabilities or delayed responses. With AI, these processes become faster, more accurate, and more automated.

Automated Threat Detection

AI-powered SASE continuously monitors network traffic, user behavior, and endpoint activity to detect security threats in real time. Using machine learning algorithms, the system can analyze vast amounts of data to identify patterns that may indicate malicious activity, such as unauthorized access attempts or abnormal traffic flows. This allows IT administrators to respond more quickly and effectively to security incidents.

Automated Incident Response

Once a security threat is identified, AI can automatically take steps to isolate or contain the threat, such as quarantining infected devices, blocking suspicious traffic, or revoking compromised credentials. These automated responses minimize the time it takes to neutralize threats and reduce the administrative burden on IT teams, enabling them to focus on strategic security improvements rather than dealing with individual incidents.

Advanced Threat Intelligence

AI-powered SASE systems leverage advanced threat intelligence gathered from a global network of sensors and security data sources. This collective knowledge helps the AI system recognize known attack vectors, such as phishing attempts or DNS-based threats, and take appropriate action before they can cause harm. By continuously learning from new data, AI improves its ability to detect and respond to emerging threats, making networks more secure over time.

5. Cost Savings and Efficiency

By reducing the need for manual intervention, improving operational efficiency, and automating complex tasks, AI-powered SASE results in significant cost savings for organizations. With AI managing routine administrative duties, IT teams can focus on higher-value activities, reducing the overhead associated with managing traditional network security systems. Additionally, AI’s ability to optimize network performance ensures that resources are used effectively, reducing wasted bandwidth and maximizing ROI on IT investments.

AI-powered SASE dramatically streamlines IT administration by automating routine tasks, providing centralized control, and enhancing security through proactive management. With the integration of AIOps, AI-driven predictive analytics, and automated remediation, organizations can ensure faster issue resolution, improved network performance, and enhanced user experience. As businesses increasingly adopt AI-powered SASE, the ability to simplify and optimize IT administration becomes a crucial factor in their ongoing success.

3. Improved User Experience: Enhancing Connectivity and Performance with AI-Powered SASE

Delivering an optimal user experience is critical for businesses to remain competitive. For many organizations, providing seamless, reliable, and secure access to applications and data—regardless of location or device—has become a major challenge.

The complexity of managing secure access, performance, and network reliability, especially for remote workforces and cloud-based environments, often creates roadblocks that degrade the user experience. AI-powered SASE (Secure Access Service Edge) addresses these challenges by using AI to optimize performance, enhance security, and provide real-time visibility into network health, all of which contribute to a vastly improved user experience.

Here, we discuss the key elements of how AI-powered SASE improves user experience by ensuring seamless, secure connectivity, proactive problem-solving, and performance optimization.

1. Real-Time Visibility and Proactive Problem-Solving

One of the most significant ways AI-powered SASE enhances the user experience is by providing real-time visibility into network performance and enabling proactive issue resolution. In a traditional network setup, IT teams often rely on manual processes and disconnected tools to diagnose and resolve problems, which can lead to delays in addressing performance bottlenecks or security incidents. However, AI-powered SASE changes this dynamic by offering continuous monitoring, instant insights, and automated remediation.

Continuous Monitoring for Performance Optimization

AI-powered SASE systems use real-time analytics to monitor network traffic, application performance, and user activity. By gathering data from all users and devices, the AI can identify network congestion, slowdowns, or disruptions as they happen. IT administrators gain immediate visibility into how specific users or applications are impacting network performance, which allows them to prioritize traffic, allocate resources more effectively, and address issues before they negatively affect the user experience.

Automated Problem Detection and Resolution

With AI’s predictive capabilities, SASE systems can detect issues even before they affect end-users. For example, if the system notices a trend of increasing latency for a specific group of users or locations, it can automatically adjust traffic routing or allocate additional bandwidth to mitigate the issue. This proactive approach helps minimize disruptions and ensures users experience minimal service interruptions, leading to higher satisfaction and productivity.

Moreover, AI can automatically resolve many common network issues without human intervention. When a problem occurs, such as packet loss or a connection drop, the AI can reroute traffic or adjust network parameters autonomously. These automated fixes reduce the burden on IT staff and ensure that users experience smooth, uninterrupted service.

2. Seamless, Efficient Connectivity for End-Users

In today’s work environment, users demand high-quality connectivity regardless of their location or the device they are using. Whether employees are working from home, accessing applications in the cloud, or collaborating across multiple regions, ensuring a seamless and secure connection is vital for business success. AI-powered SASE enables efficient and consistent connectivity by leveraging its AI-driven networking capabilities.

Optimized Traffic Routing

AI-powered SASE solutions enhance user connectivity by optimizing how traffic flows across the network. Traditionally, traffic routing decisions are based on static configurations and manual rules. However, AI enables dynamic and intelligent routing decisions based on real-time data and network conditions. For instance, if a user’s device is experiencing slow access to a cloud application due to network congestion, AI can automatically re-route the traffic through a faster or less congested network path, ensuring minimal delay.

By continuously analyzing traffic patterns, AI can ensure that end-users are connected to the most optimal resources, reducing latency and improving application performance. Whether users are connecting from a branch office, remote location, or the cloud, AI-driven routing ensures that they get the best possible performance.

Optimized Bandwidth Usage

Another aspect of AI-powered SASE that improves user experience is its ability to optimize bandwidth usage. In modern networking, bandwidth is a precious resource that must be efficiently allocated across a variety of applications, devices, and locations.

AI can monitor bandwidth consumption and adjust allocations based on priority, ensuring that mission-critical applications receive the resources they need while non-essential traffic is deprioritized. For example, if an employee is streaming video content during a critical video conference, the AI can intelligently reduce bandwidth for the video stream to ensure high-quality communication for the meeting.

By effectively managing bandwidth resources, AI helps avoid network slowdowns or bottlenecks, ensuring that users can access applications quickly and efficiently.

3. Seamless User Access Across Devices and Locations

With the rise of remote work, employees are often accessing networks and applications from a variety of devices, including laptops, smartphones, and tablets. This means that users’ access needs to be highly flexible while maintaining security and performance. AI-powered SASE excels in enabling seamless, secure access to resources regardless of where users are located or what device they are using.

Zero Trust Network Access (ZTNA) for Secure Connectivity

AI-powered SASE integrates Zero Trust principles, ensuring that access to network resources is only granted after continuous verification, regardless of location or device. This means that users are constantly authenticated and authorized before accessing sensitive applications, minimizing the risk of unauthorized access. By combining AI with ZTNA, organizations can provide secure, frictionless access to users without compromising performance.

Additionally, the AI-driven system continuously monitors user behavior and network interactions to detect any abnormal activity, ensuring that users have uninterrupted access to resources while preventing security threats. For example, if an employee’s credentials are compromised, the AI can detect unusual behavior patterns (such as accessing resources outside of normal working hours or from a different location) and block or restrict access accordingly.

Consistency Across Devices

With AI-powered SASE, users benefit from a consistent experience across devices, whether they’re using a corporate laptop, a mobile phone, or a tablet. The AI system ensures that security policies, bandwidth allocation, and performance optimizations are applied uniformly across all devices, creating a seamless user experience. This consistency is crucial in a multi-device environment, as it ensures that users can switch between devices without encountering performance drops or access issues.

4. AI-Driven Personalization of User Experience

An additional benefit of AI in enhancing user experience is its ability to personalize network performance. AI-powered SASE platforms can continuously learn from user behavior and preferences, and use this data to optimize network performance based on individual needs.

Personalized Application Performance

Through machine learning, AI can understand which applications are most critical to a specific user or group of users. For example, if a sales team is highly dependent on cloud-based CRM software, the AI can prioritize bandwidth for this application, ensuring that the team always has fast, reliable access to the tools they need to do their jobs. Similarly, the AI can de-prioritize non-essential applications, such as social media or video streaming, during working hours to ensure optimal performance for critical business functions.

This level of personalization creates a more efficient and user-friendly network environment, helping employees stay productive and engaged.

5. Seamless Integration with Cloud Applications

As organizations continue to migrate to the cloud, users need uninterrupted access to a growing array of cloud applications. AI-powered SASE ensures that users can securely and efficiently access these applications without performance degradation or delays.

Optimized Cloud Access

AI ensures that traffic to cloud applications is routed efficiently, taking into account factors such as network congestion, geographical location, and resource availability. This ensures that users experience fast access to cloud-based tools and services, no matter where they are located. Furthermore, by using AI to optimize traffic flow to cloud environments, organizations can mitigate latency issues that commonly affect users connecting to cloud-hosted applications.

AI-powered SASE significantly enhances the user experience by improving performance, providing real-time visibility, enabling seamless connectivity, and automating issue resolution. Through intelligent traffic routing, automated problem-solving, and personalized network optimizations, AI-driven SASE ensures that end-users can access applications securely and with minimal delays.

As remote work becomes more prevalent and cloud adoption continues to rise, the need for seamless, secure, and high-performance networks has never been greater. AI-powered SASE not only addresses these needs but also elevates the user experience to new heights, enabling organizations to remain agile, efficient, and competitive.

4. Scalability and Adaptability: Flexibility to Scale with Business Needs, Including Remote Workforces and New Locations

As organizations grow, their network needs evolve. With the rise of remote workforces, cloud services, and global operations, businesses need networking solutions that are flexible, scalable, and adaptable to changing demands. AI-powered SASE delivers on this requirement by offering unparalleled scalability and adaptability, ensuring that organizations can easily accommodate new users, locations, or services without compromising security or performance.

One of the primary advantages of AI-enhanced SASE solutions is their ability to scale seamlessly. Traditional network infrastructures often require significant manual effort and hardware upgrades to scale up. With SASE, however, AI-powered systems are designed to handle increasing workloads and the growing demands of modern business environments.

Whether an organization is opening a new office, expanding its global reach, or onboarding a new team of remote workers, the system can quickly adapt to the new requirements without significant additional investment in physical infrastructure.

For remote workforces, scalability is particularly important. The shift to remote and hybrid work models has created a need for secure, high-performing networks that can support employees regardless of their location. AI-powered SASE solutions facilitate this by offering secure, optimized access to corporate resources from anywhere. AI can intelligently route traffic based on real-time conditions and user locations, ensuring that remote employees have the same level of connectivity and security as those working in the office.

Moreover, as organizations expand into new regions or adopt new technologies, SASE platforms can dynamically adjust to the new network architecture. For example, AI can optimize routing to new cloud services, adjusting bandwidth allocations and network paths to ensure optimal performance and security. This adaptability helps businesses stay agile and responsive in a fast-paced digital environment, where change is constant and unpredictable.

Another critical aspect of scalability in AI-powered SASE is the ease with which organizations can manage and monitor their networks as they grow. Through centralized dashboards and AI-driven insights, administrators can monitor the entire network from a single interface, regardless of the number of users or locations. This centralized approach to management allows organizations to scale their operations without being overwhelmed by complexity or administrative burden.

In conclusion, the scalability and adaptability of AI-powered SASE platforms allow organizations to grow and evolve with ease. Whether expanding remote work capabilities, adding new locations, or adopting emerging technologies, businesses can rely on SASE to deliver the performance, security, and flexibility needed to support growth.

5. Better Network Performance: AI-Enabled Optimization of Traffic and Resources

Network performance is critical to the success of any business, particularly in an era where digital transformation and cloud adoption are integral to operations. AI-powered SASE solutions improve network performance by intelligently optimizing traffic and resource allocation, ensuring that businesses can deliver fast, reliable services to users and customers.

One of the key ways AI enhances network performance is through intelligent traffic routing. Traditional network architectures often rely on static configurations that do not account for fluctuations in network demand or user behavior.

In contrast, AI-powered SASE solutions continuously analyze network traffic in real-time and dynamically adjust routing to optimize bandwidth usage and minimize latency. For instance, AI can prioritize time-sensitive applications, such as video conferencing or VoIP calls, while ensuring that less critical traffic does not overwhelm the network.

Another benefit of AI in optimizing network performance is its ability to predict traffic patterns based on historical data. By learning from past usage trends, AI algorithms can proactively adjust resources before performance degradation occurs. This predictive capability ensures that businesses can stay ahead of traffic spikes or unexpected surges in demand, maintaining a smooth and uninterrupted experience for users.

AI-powered SASE systems also enable more efficient use of network resources. Through automated load balancing and intelligent bandwidth management, these platforms can ensure that network resources are allocated based on real-time needs.

For example, if a particular office or location experiences heavy traffic, the AI system can automatically reallocate resources to ensure that other parts of the network are not impacted. This optimization minimizes congestion and ensures that critical services are always available, even during peak usage periods.

Additionally, AI-powered SASE can reduce network latency by optimizing routing paths and minimizing the number of hops data must take to reach its destination. Latency reduction is especially important for businesses that rely on cloud-based applications or real-time communication tools. By ensuring that data travels through the fastest and most efficient routes, AI-powered SASE minimizes delays and improves the overall user experience.

In summary, AI-powered SASE solutions enhance network performance by optimizing traffic, predicting patterns, and intelligently managing resources. These capabilities ensure that businesses can deliver fast, reliable, and efficient services, improving productivity and customer satisfaction.

F. Consistent Visibility and Smarter Decision-Making: Centralized Monitoring and Management Through Integrated Dashboards

Effective decision-making in network management requires accurate and up-to-date insights. AI-powered SASE solutions provide organizations with consistent visibility into their network performance, security, and user activity through centralized dashboards. These integrated platforms offer administrators a unified view of their entire network, enabling smarter, data-driven decisions.

Centralized monitoring is a significant advantage for IT teams managing complex, multi-site, or hybrid environments. With AI-powered SASE, all network data flows through a single platform, where it can be analyzed, visualized, and acted upon. This centralized approach eliminates the need for IT administrators to juggle multiple tools and interfaces, streamlining management and improving efficiency.

Furthermore, AI-driven insights enhance decision-making by identifying trends, potential issues, and opportunities for improvement. Machine learning algorithms can analyze vast amounts of data to uncover patterns that may not be immediately obvious.

For instance, AI can detect anomalies in user behavior, network traffic, or application performance, alerting administrators to potential security threats or areas where optimization is needed. These proactive insights allow organizations to address issues before they become critical, improving both security and performance.

AI can also help with capacity planning and resource allocation by analyzing historical data to predict future needs. For example, if an organization is planning to scale its operations, AI-powered SASE can provide recommendations on how to adjust network resources to accommodate the increased load. These data-driven recommendations enable organizations to make informed decisions that align with their long-term goals.

In conclusion, AI-powered SASE provides consistent visibility and smarter decision-making through centralized monitoring and data-driven insights. This enhanced visibility enables IT teams to manage networks more effectively, respond to threats proactively, and make better decisions that align with organizational goals.

G. Cost Efficiency: Reduced Hardware Dependence and Operational Overhead

Cost efficiency is a top priority for most organizations, and AI-powered SASE solutions contribute to this goal by reducing hardware dependence, lowering operational overhead, and optimizing resource utilization.

Traditional network architectures often require significant investment in hardware, such as routers, firewalls, and other security appliances. These devices are typically costly to purchase, maintain, and upgrade. With SASE, however, many of these hardware components are replaced by cloud-based services and AI-driven software solutions. This reduces the need for physical infrastructure, cutting down on capital expenditures and minimizing ongoing maintenance costs.

AI-powered SASE also contributes to cost efficiency by automating routine network management tasks. Through machine learning and automation, SASE platforms can handle tasks such as traffic routing, security monitoring, and incident response without requiring constant human intervention. This reduces the workload on IT teams, freeing them up to focus on more strategic initiatives.

Additionally, the ability to automate troubleshooting and resolve common issues quickly ensures that resources are utilized efficiently, and downtime is minimized.

Finally, AI-powered SASE optimizes resource allocation by ensuring that network resources are only used when and where they are needed. For example, if a particular location or user group experiences low network traffic, the system can dynamically reduce resource allocation, leading to more efficient use of bandwidth and computing power. This optimization results in lower operational costs and a more sustainable network architecture.

In conclusion, AI-powered SASE enhances cost efficiency by reducing hardware requirements, automating routine tasks, and optimizing resource utilization. This results in lower capital expenditures, reduced operational overhead, and better resource management, ultimately leading to cost savings for organizations.

Real-World Applications and Use Cases of AI-Powered SASE

AI-powered Secure Access Service Edge (SASE) is transforming how organizations manage their networks, particularly in industries that face complex security, connectivity, and scalability challenges. As digital transformation accelerates, businesses are looking for solutions that can deliver secure, scalable, and high-performance networking.

AI-driven SASE offers critical advantages to a wide range of industries, improving efficiency, security, and user experience. Let’s explore real-world applications and use cases where AI-powered SASE provides significant benefits.

1. Healthcare Industry: Enhancing Data Security and Connectivity

The healthcare industry deals with a massive amount of sensitive data, including personal health information (PHI) protected by stringent regulations like HIPAA (Health Insurance Portability and Accountability Act). AI-powered SASE solutions help healthcare organizations ensure secure access to sensitive data and applications across distributed environments, such as hospitals, clinics, and remote healthcare workers.

In healthcare, AI-powered SASE can provide granular visibility into network traffic, ensuring compliance with regulations and preventing unauthorized access to sensitive data. For example, AI systems can identify abnormal user behavior, such as a healthcare worker accessing patient records they are not authorized to view, and trigger real-time alerts or automatic response actions to prevent potential breaches.

Moreover, AI-driven SASE helps optimize network performance for telemedicine applications, which rely on fast, uninterrupted video conferencing and data transfers. By intelligently routing traffic and prioritizing high-bandwidth applications, SASE ensures that remote consultations are seamless and that patient data is transmitted securely and quickly.

A case study in this context could involve a large healthcare provider using AI-powered SASE to streamline remote work for doctors and nurses. With many employees working remotely or in satellite locations, the organization faced challenges in maintaining secure, high-performance access to healthcare applications. By implementing AI-driven SASE, they were able to optimize network performance, provide secure access, and ensure that healthcare workers could collaborate without latency or security concerns.

2. Financial Services: Securing Remote Access and Regulatory Compliance

In the financial services sector, security is paramount. Financial institutions are often the targets of sophisticated cyberattacks, and their networks must be protected to prevent data breaches, financial fraud, and loss of customer trust. Additionally, financial organizations must comply with regulations such as the GDPR (General Data Protection Regulation) and PCI DSS (Payment Card Industry Data Security Standard).

AI-powered SASE is a game-changer in financial services by offering robust security mechanisms such as secure access, threat detection, and continuous monitoring. AI algorithms analyze network traffic in real time to identify anomalies or signs of malicious activity. For example, if an employee attempts to access a sensitive financial application from an unrecognized device or location, AI-driven SASE can block access, notify administrators, and require additional authentication.

Furthermore, the need for secure remote access has skyrocketed in the financial industry as hybrid and remote work models have become more common. AI-powered SASE provides seamless, secure access to critical financial applications regardless of where employees are located. It dynamically adjusts network routes and policies based on real-time data, ensuring that financial professionals working remotely can access the applications they need without compromising security.

A real-world example could involve a global bank that implemented AI-powered SASE to protect their network as they scaled their remote workforce. By using AI-driven threat detection and secure access capabilities, the bank significantly reduced its vulnerability to cyberattacks while providing secure and efficient access to remote employees working from various locations around the world.

3. Retail: Optimizing Customer Experience and Supply Chain Operations

In the retail industry, providing an excellent customer experience is key to maintaining brand loyalty and driving revenue. AI-powered SASE plays an important role in optimizing e-commerce platforms, ensuring that customers enjoy fast, secure, and reliable access to online stores.

AI-driven SASE solutions help retailers optimize network traffic, reduce latency, and ensure fast page load times for customers shopping online. For example, AI can route web traffic efficiently based on real-time conditions and ensure that critical e-commerce applications remain available even during high-traffic events, such as Black Friday or seasonal sales.

By optimizing the delivery of content and resources, SASE ensures that customers can access product information and make purchases without delays, improving their overall shopping experience.

Additionally, AI-powered SASE helps retailers manage their supply chain more effectively by providing secure, optimized access to supply chain management applications. With multiple locations and suppliers, it is crucial for retailers to ensure secure and efficient communication between their warehouses, distribution centers, and external vendors. AI-driven SASE can provide real-time visibility into supply chain traffic, preventing disruptions and ensuring that the right information reaches the right stakeholders at the right time.

A case study could involve a major retail chain that adopted AI-powered SASE to improve the performance and security of their e-commerce platform. By implementing SASE to optimize web traffic and ensure secure transactions, the retailer saw a significant increase in customer satisfaction and conversion rates, while also protecting sensitive customer data from potential breaches.

4. Manufacturing: Securing Industrial IoT and Optimizing Operational Efficiency

The manufacturing sector is increasingly adopting smart technologies, such as Industrial Internet of Things (IIoT) devices, to improve operational efficiency, reduce downtime, and monitor equipment performance. However, these connected devices introduce new security vulnerabilities that must be addressed to ensure safe and efficient operations.

AI-powered SASE provides manufacturing companies with the ability to secure their IIoT networks and ensure that data from connected devices is transmitted securely and efficiently. AI-driven threat detection algorithms continuously monitor the network for suspicious activity, ensuring that unauthorized devices are prevented from accessing critical systems or sensitive data.

In addition, AI-powered SASE solutions help manufacturers optimize the performance of their IIoT devices by intelligently managing bandwidth and prioritizing traffic. By ensuring that critical devices, such as factory sensors or machinery, always have the necessary resources, manufacturers can reduce operational delays and improve productivity.

A case study in this field could involve a global manufacturer implementing AI-powered SASE to secure its IIoT network across multiple production facilities. By using SASE to monitor and optimize network traffic, the company was able to prevent potential security threats while ensuring that critical operational data from IIoT devices was transmitted in real time, improving the overall efficiency of their operations.

5. Education: Supporting Remote Learning and Ensuring Data Privacy

The education sector is another area where AI-powered SASE is having a profound impact. As educational institutions adopt more online and hybrid learning models, the need for secure, scalable, and high-performance networking solutions has never been greater.

AI-powered SASE helps educational institutions ensure secure access to learning platforms, both for students and faculty members. By providing secure, optimized connections for users across various locations and devices, SASE ensures that online learning tools function smoothly, enabling uninterrupted learning experiences.

Furthermore, educational institutions are tasked with protecting student data, which is often subject to privacy regulations like FERPA (Family Educational Rights and Privacy Act). AI-powered SASE solutions offer real-time monitoring and threat detection, ensuring that only authorized users have access to sensitive student data. AI can also help identify and respond to potential data breaches, minimizing the risk of privacy violations.

A case study could involve a university that implemented AI-powered SASE to secure its remote learning infrastructure. By optimizing network traffic and providing secure access for students and faculty members, the university was able to ensure a seamless learning experience while maintaining compliance with privacy regulations.

The Future of AI-Powered SASE

The future of AI-powered Secure Access Service Edge (SASE) is poised to redefine how organizations manage their networks, particularly as the digital landscape continues to evolve. As businesses increasingly adopt cloud-based infrastructures, remote work models, and Internet of Things (IoT) devices, AI-powered SASE will play an even more critical role in securing and optimizing network performance.

Emerging trends such as natural language processing (NLP), predictive analytics, and advanced automation are expected to revolutionize the capabilities of AI-powered SASE, addressing the evolving needs of businesses in the face of growing cyber threats and networking challenges.

1. Emerging Trends: Natural Language Processing, Predictive Analytics, and Advanced Automation

As AI continues to advance, we can expect to see more sophisticated technologies incorporated into SASE platforms, enabling organizations to achieve even greater levels of automation, optimization, and decision-making support.

Natural Language Processing (NLP) is one such trend. NLP allows machines to understand and interpret human language, making it easier for administrators to interact with AI-powered SASE systems. For example, an administrator could use natural language queries to request insights or make configuration changes, significantly reducing the complexity of managing the network. With NLP, AI systems will be able to translate complex network conditions into understandable terms, providing actionable insights that are accessible to non-technical users.

Predictive analytics is another powerful trend shaping the future of AI-powered SASE. By analyzing historical data and identifying patterns, AI can predict future network behavior and potential issues. Predictive analytics enables organizations to proactively address problems before they occur, improving performance and minimizing downtime. For instance, predictive models can anticipate traffic spikes, network congestion, or security threats, allowing administrators to take preventative actions to avoid disruption.

Advanced automation is also expected to play a significant role in the future of AI-powered SASE. As networks become more complex and dynamic, the need for intelligent automation will increase. AI will continue to automate routine tasks such as traffic routing, security enforcement, and incident response, freeing up IT teams to focus on strategic initiatives. Advanced automation will enable self-healing networks, where SASE platforms can autonomously adjust resources, reroute traffic, and mitigate threats without human intervention.

2. The Growing Importance of AI in Addressing Evolving Cyberthreats and Networking Challenges

Cybersecurity is one of the biggest challenges facing organizations today. With the increasing sophistication of cyberattacks, businesses need to be proactive in their defense strategies. AI-powered SASE is at the forefront of addressing evolving cyberthreats, offering real-time threat detection, automated responses, and continuous monitoring.

AI algorithms are capable of identifying and responding to threats much faster than traditional security tools. By analyzing large volumes of network traffic in real time, AI-powered SASE platforms can detect anomalies such as unauthorized access attempts, data exfiltration, or advanced persistent threats (APTs). AI can also enhance threat intelligence by correlating data from multiple sources, providing a more comprehensive understanding of the threat landscape.

As organizations adopt more cloud-based and distributed architectures, network security becomes increasingly complex. AI-powered SASE simplifies this by offering a unified security model that spans on-premises, cloud, and remote environments. By automating security policies and enforcing them consistently across the network, SASE ensures that organizations can manage security at scale, without sacrificing performance.

3. Potential for Broader Adoption Across Industries

The potential for broader adoption of AI-powered SASE is significant. As organizations continue to embrace cloud technologies, remote work, and digital transformation, the need for secure, scalable, and high-performance networking solutions will only grow. Industries such as healthcare, finance, retail, manufacturing, and education are already seeing the benefits of AI-powered SASE, but the technology’s reach will expand across other sectors as well.

In the coming years, we can expect AI-powered SASE to become the standard for network security and optimization. As AI and machine learning technologies continue to evolve, the capabilities of SASE platforms will expand, enabling organizations to address even more complex networking challenges. With its ability to provide secure, seamless, and efficient connectivity, AI-powered SASE is poised to become an essential tool for businesses looking to thrive in the digital era.

In conclusion, AI-powered SASE is the future of network security and optimization. As emerging trends such as natural language processing, predictive analytics, and automation take hold, the capabilities of SASE platforms will continue to evolve, helping organizations address the growing challenges of cybersecurity, connectivity, and scalability. The widespread adoption of AI-powered SASE across industries is inevitable, as businesses recognize its ability to deliver enhanced security, performance, and efficiency in an increasingly digital world.

Conclusion

It may seem counterintuitive to trust AI with the critical task of managing network security and performance, yet AI-powered SASE is quickly proving itself as the most reliable solution for modern organizations. The combination of secure, optimized, and scalable connectivity that SASE offers, backed by the intelligence of AI, makes it an indispensable tool for businesses in today’s rapidly evolving landscape.

As digital transformation accelerates and businesses increasingly rely on cloud services, AI-powered SASE enables organizations to seamlessly adapt to new challenges while enhancing overall operational efficiency. Looking ahead, this innovation presents an opportunity for businesses to streamline their security and network management processes while positioning themselves for growth.

To stay ahead in a cloud-driven world, organizations must embrace AI-powered SASE as an integral part of their IT strategy. The first step is assessing their current network infrastructure to identify gaps in performance, security, and scalability that AI-powered SASE can address.

Second, organizations should explore a phased implementation of SASE, starting with a focus on high-priority use cases like secure remote work or cloud application optimization.

By doing so, companies can harness the power of AI to drive proactive decision-making, enhance user experiences, and safeguard their networks against an ever-growing array of cyber threats. The future belongs to those who adopt AI-powered SASE as an essential enabler of their digital success.

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