Digital Version Artificial intelligence is moving far beyond experimentation. Enterprises are no longer exploring isolated use cases or testing proof of concepts; they are embedding intelligent systems into decisions that influence customers, operations, financial outcomes, and long term strategy. As AI becomes increasingly autonomous, however, one challenge has emerged above all others. The question is no longer how intelligent these systems can become, but how organisations can ensure they remain accountable, transparent, and worthy of trust once they begin operating at scale. For Dr. Brindha Jeyaraman, Founder and CEO of Aethryx, solving that challenge has become both a professional mission and an entrepreneurial purpose. Over nearly two decades, she has built an exceptional career spanning artificial intelligence, data engineering, cloud platforms, enterprise architecture, and AI governance within highly regulated financial environments. Working across engineering, architecture, and governance gave her an unusually comprehensive perspective on enterprise AI. She learned that building intelligent systems was only one part of the equation. Ensuring those systems could be governed responsibly, aligned with business objectives, and trusted by both organisations and regulators was equally critical. That understanding continues to shape not only her leadership philosophy but also the vision behind Aethryx. The inspiration to establish the company emerged from a recurring challenge she encountered throughout her career. As organisations accelerated their adoption of generative and agentic AI, governance practices remained largely dependent on manual reviews, fragmented documentation, and periodic compliance exercises. Those approaches were designed for traditional systems, not for AI agents capable of planning, interacting with external tools, exchanging information, and making decisions in real time. The gap between technological progress and governance readiness was becoming increasingly difficult to ignore. Rather than accepting it as an industry limitation, Dr. Brindha recognised it as an opportunity to build the missing operational layer that modern enterprises urgently needed. Founded on that conviction, Aethryx is developing practical infrastructure that enables organisations to automate AI risk and compliance while governing intelligent agents throughout their execution. Its approach transforms responsible AI from a collection of policies into an operational capability embedded directly within enterprise workflows. By helping organisations strengthen oversight, automate governance, monitor agent behaviour, and generate continuous evidence of compliance, Aethryx empowers businesses to innovate with confidence instead of uncertainty. Under Dr. Brindha’s leadership, the company is contributing to a future where governance evolves alongside intelligence, enabling enterprises to scale AI responsibly rather than forcing them to choose between innovation and accountability. Behind this vision lies a leadership philosophy shaped not by industry trends, but by years of practical experience across the full lifecycle of enterprise AI. Throughout her journey, Dr. Brindha repeatedly observed that lasting innovation depends on far more than sophisticated models or advanced technology. It requires disciplined engineering, clear governance, cross functional collaboration, and a deep understanding of how AI creates value within real organisations. Those principles continue to guide both her leadership and Aethryx’s growth, positioning the company at the forefront of one of artificial intelligence’s most important priorities: building the trust infrastructure that will enable intelligent innovation to flourish for years to come. Where Technology Meets Accountability Every stage of Dr. Brindha’s career added a new perspective to how artificial intelligence creates value inside large organisations. She has contributed to the design of production AI systems, built enterprise scale cloud and data platforms, and led AI governance initiatives within highly regulated financial institutions. Rather than seeing these as separate disciplines, she came to understand that they form different parts of the same ecosystem. A technically sophisticated model delivers limited business value if it cannot be deployed reliably, understood by decision makers, or governed consistently throughout its lifecycle. Working across diverse transformation programmes also exposed her to the difference between successful innovation and innovation that struggles to scale. Some organisations invested heavily in advanced technologies yet found themselves constrained by fragmented governance, disconnected processes, or limited visibility into how AI systems were operating after deployment. Others achieved stronger outcomes because engineering, business strategy, risk management, and governance evolved together from the beginning. Those experiences reinforced an important belief that continues to shape her leadership today: sustainable innovation is built by integrating technology, people, processes, and accountability rather than treating them as independent priorities. That understanding became even more significant as generative and agentic AI began transforming enterprise environments. Unlike earlier AI applications that primarily generated insights for human review, modern AI agents increasingly plan tasks, access enterprise systems, coordinate with other agents, and execute multi step activities with growing levels of autonomy. While these capabilities create enormous opportunities for productivity and business transformation, they also introduce new questions around permissions, oversight, security, explainability, and accountability. Dr. Brindha recognised that enterprises needed more than stronger AI models. They needed an entirely new operational approach to governing intelligent systems as they worked in real time. It was this industry shift that inspired the evolution of Aethryx from an entrepreneurial vision into a purpose driven technology company. Rather than adding another governance framework or compliance checklist, Aethryx is focused on building the operational infrastructure that allows organisations to innovate responsibly without slowing progress. Its AI Governance Automation Platform enables enterprises to automate AI inventories, risk assessments, regulatory mappings, approvals, attestations, and audit evidence, helping governance become an integrated business capability instead of a manual administrative process. Complementing this is AssureTrust, the company’s runtime governance platform, which monitors AI agents during execution, evaluates changing risk, enforces permissions and policies, introduces human approval where required, and creates continuous evidence of how important AI driven decisions are made. For Dr. Brindha, this represents a fundamental shift in how responsible AI should be approached. Governance should not exist as documentation created after technology has already been deployed. It should operate alongside intelligent systems, continuously adapting as those systems evolve. By embedding governance directly into enterprise operations, organisations gain the confidence to innovate faster while maintaining transparency, regulatory readiness, and meaningful human oversight. In her view, the organisations that lead the next generation of AI will not simply be those developing the most

Digital Version The food and beverage industry stands at a pivotal moment in its evolution. Across the globe, manufacturers are being challenged to produce more efficiently, operate more sustainably, maintain uncompromising quality standards, strengthen cybersecurity, and adapt to increasingly dynamic consumer demands. At the same time, technologies such as artificial intelligence, edge computing, digital twins, and smart manufacturing are transforming what is possible on the factory floor. Yet amid the excitement surrounding these innovations, one critical reality is often overlooked: technology alone does not drive transformation. For Peter Kneski, Solution Consultant Practice Leader at Belden Inc., the true differentiator is not the latest technology trend but the foundation that supports it. Throughout his career, Peter has worked closely with organizations seeking to modernize operations and unlock the full potential of digital transformation. In that journey, he has witnessed a recurring pattern. Companies frequently invest in promising technologies only to discover that their existing infrastructure is not prepared to support them at scale. The result is often stalled initiatives, failed pilots, and unrealized expectations. This perspective has shaped Peter’s approach to leadership and innovation. Rather than focusing solely on the technologies that capture headlines, he encourages organizations to think more deeply about how information flows through their operations, how systems communicate, and how infrastructure supports long-term growth. His philosophy is both practical and forward-looking: when the foundation is strong, innovation becomes sustainable, scalable, and capable of delivering measurable business value. At Belden, Peter operates at the intersection of operational technology, industrial networking, cybersecurity, and digital transformation. This unique vantage point allows him to help manufacturers navigate some of the industry’s most pressing challenges while preparing for a future that is becoming increasingly connected, intelligent, and data-driven. His work is not simply about implementing technology; it is about helping organizations create the conditions that allow technology to thrive. In an industry where quality, efficiency, resilience, and sustainability have become inseparable priorities, Peter’s insights offer a compelling blueprint for what comes next. Leading Beyond Technology One of the reasons Peter’s perspective resonates so strongly within the manufacturing sector is that it is rooted in practicality rather than hype. While many conversations about digital transformation focus on ambitious visions of the future, Peter believes successful leadership begins with understanding the details. For him, innovation is not about adopting technology because it is trending. It is about understanding how technology functions, how it aligns with operational objectives, and how it creates measurable value. This disciplined approach has become one of the defining characteristics of his leadership philosophy. In highly regulated industries such as food and beverage manufacturing, where quality, safety, compliance, and consistency are paramount, leaders cannot afford to make decisions based on assumptions. Every investment must be evaluated carefully. Every solution must be examined critically. Every initiative must have a clear purpose. Peter often emphasizes the importance of continually asking the right questions. How will this technology improve operations? Why is it necessary? What outcomes should be expected? What happens if conditions change? These questions help organizations move beyond marketing promises and focus on practical results. Equally important is the role of partnerships. Digital transformation rarely happens in isolation. Manufacturers frequently rely on external organizations to provide expertise, technology, and support. However, Peter believes selecting a partner involves much more than evaluating products or technical capabilities. Culture matters. Values matter. Commitment matters. The strongest partnerships are built when organizations share a common purpose and a genuine desire to create value together. Peter has consistently found that technology providers who demonstrate passion, accountability, and a deep understanding of their customers’ challenges are often the ones who deliver the most meaningful results. This people-first approach has become increasingly important as organizations navigate complex transformation journeys. Technology may enable progress, but trust, collaboration, and shared vision are often what make that progress possible. Reimagining Manufacturing Through Digital Transformation Few developments have influenced modern manufacturing as profoundly as digital transformation. What was once viewed as a collection of disconnected technologies has evolved into a strategic framework for improving performance across every aspect of the business. Peter has observed this evolution firsthand. In his view, one of the most significant impacts of digital transformation has been the way manufacturers interpret and utilize operational data. Historically, many organizations relied on delayed reporting, fragmented information, and limited visibility into production environments. Decision-making often depended on historical trends rather than real-time insights. While these approaches served their purpose, they left significant opportunities for optimization untapped. Today, digital transformation is changing that reality. Modern manufacturing environments generate enormous volumes of operational data. When properly collected, contextualized, and analyzed, this information becomes a powerful tool for improving efficiency, consistency, and performance. Within the food and beverage sector, throughput remains one of the most important drivers of operational success. Manufacturers constantly seek ways to increase production while maintaining quality standards and controlling costs. Digital transformation provides unprecedented visibility into these objectives. Organizations can now compare throughput across facilities, monitor utility consumption, evaluate production efficiency, and maintain quality consistency across diverse manufacturing environments. Instead of viewing these metrics independently, they can analyze them collectively, revealing relationships and opportunities that were previously difficult to identify. This holistic perspective enables better decision-making at every level of the organization. Leaders gain greater confidence in strategic planning, managers receive faster access to operational insights, and frontline teams benefit from clearer visibility into performance. For Peter, the true power of digital transformation lies in its ability to turn data into actionable intelligence. It is not simply about collecting information; it is about creating the clarity needed to drive meaningful improvement. Why Edge Computing Is Becoming a Game-Changer As manufacturers continue to expand their digital capabilities, the volume of data generated throughout production environments continues to grow. Managing this information efficiently has become one of the industry’s most important challenges. Among the technologies reshaping this landscape, Peter identifies edge computing as one of the most impactful developments in recent years. Traditionally, manufacturing systems transmitted large volumes of operational data directly to