Archive360 In the Media

In this AI Journal article, George Tziahanas, VP of Compliance at Archive360, explores one of the biggest hidden risks in enterprise AI adoption: false or misleading insights driven by ungoverned or outdated data. He highlights why “data quality debt” is a growing threat for organisations racing to deploy GenAI and outlines five key steps to strengthen transparency, authenticity, and control across AI data pipelines. Essential reading for leaders looking to make AI trustworthy, compliant, and truly valuable.

Featured in Nutanix’s “The Forecast,” this article by Gary Hilson explores how artificial intelligence is transforming data storage architecture, driving new demands for scalability, performance, and efficiency in a rapidly evolving digital ecosystem. The piece also includes insights from Archive360’s VP of Compliance, highlighting how governance and security play a critical role in the AI era.

In an article from Insurance Edge, George Tziahanas, VP of Compliance at Archive360, explores how building strong data foundations empowers insurers to scale AI initiatives, improve governance, and achieve real business impact.

In an article from SiliconANGLE, information archiving and management platform company Archive360 Inc. announced a new collaboration with Microsoft Corp. to deliver AI-powered eDiscovery and compliance solutions. This collaboration combines advanced AI with trusted data governance to help organizations manage, discover, and protect information more efficiently and securely.

In an article from PropertyCasualty360, Archive360’s George Tziahanas explores why modern data governance is essential for transparency, trust, and innovation as AI reshapes the insurance industry. His insights highlight how insurers can balance compliance and agility in the AI era.

Silicon UK explores why competing on speed, scale, and insight is no longer optional. In the feature, Archive360's George Tziahanas highlights how the real differentiator is whether governance is treated as a brake or an accelerator, and why archived and legacy data remain among the most untapped opportunities in enterprise AI.