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Aviz enhances visibility into AI traffic with advanced DPI engine.

Source Decision Insights Coverage Published November 17, 2025 Companies 4
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4 companies named across 14 categories, one of 47 articles referencing DEEP. Previous coverage: Aviz Networks enhances 5G monitoring and AI management solutions - October 2025 (Nov 2025).

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Recent advancements in Artificial Intelligence (AI) are impacting enterprise operations significantly, but they also create visibility issues for IT and security teams. Traditional Deep Packet Inspection tools fall short in monitoring encrypted or API-driven AI traffic, resulting in potential compliance and security challenges. Aviz's updated Deep Packet Inspection (DPI) engine, integrated within the Aviz Service Node, aims to address these gaps by delivering real-time insights into both sanctioned and shadow AI applications across various infrastructures.

AI Boom vs. Visibility Challenges

As AI technologies proliferate within enterprises, their integration into workflows has accelerated. Projections indicate that conversational AI will be included in a substantial portion of enterprise applications by 2024, and a majority of employees may use unauthorized AI tools by 2027. This growth brings with it heightened security concerns.

Statistics from Cyberhaven indicate that a majority of enterprise AI tools represent high-risk factors, and many AI applications operate without official approval, complicating oversight. Given the distributed nature of AI applications, enforcing governance across platforms has become increasingly complex, and legacy Deep Packet Inspection (DPI) solutions struggle to adapt to modern traffic patterns.

Understanding Shadow AI

Shadow AI consists of AI applications utilized outside the purview of IT departments, creating potential risks within enterprise operations. Common examples include popular AI tools like ChatGPT and Copilot.

Risks Associated with Shadow AI

  • Data Privacy Issues: Sensitive information may inadvertently be exposed through unauthorized use of AI models.
  • Security Vulnerabilities: Uncontrolled interactions with AI applications may introduce points of exploitation.
  • Compliance Risks: Use of unofficial AI solutions may breach internal regulations and client agreements.
  • Infrastructure Complexity: Shadow AI traffic often traverses multiple environments, eluding standard monitoring techniques.

The limitations of existing DPI solutions, which rely heavily on static identifiers, hinder effective tracking of this dynamic AI traffic.

The Aviz Service Node aims to improve this situation with its next-generation DPI engine, designed specifically for today's AI environments.

Features of the Aviz Service Node

The Aviz Service Node operates as a high-performance software appliance, providing extensive visibility into AI traffic across diverse network environments.

Its advanced DPI engine is tailored for the encrypted traffic characteristic of modern AI applications. By performing a comprehensive analysis of packet information, it achieves accurate identification of both sanctioned and unsanctioned AI tools in operation.

Enhanced Application Detection

This DPI solution is capable of analyzing not just headers but the actual payload and contextual data, allowing clear identification of applications even in encrypted conditions.

Comprehensive Monitoring and Visualization

All data gathered by the Aviz Service Node is relayed to the Aviz Elastic Node, which serves as the base for analytics and visualization.

This setup provides network and security teams with insights into AI traffic activities and application usage across the enterprise.

Conclusion

The emergence of AI technologies presents new challenges for enterprises regarding visibility and control. Shadow AI may represent substantial compliance and security risks, while traditional DPI tools lack the capacity to effectively monitor AI-driven traffic.

Aviz's next-generation DPI engine addresses these challenges by enabling real-time, detailed oversight into AI applications across network infrastructures, supporting responsible AI governance and usage.

Blog post, originally published by Ram Mohan Hariprasad at Aviz Networks.

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