A Highly Scalable Architecture For AI-First Semiconductor Operations
At the PDF Solutions CONNECT event to be held on October 15–16 in San Francisco, PDF Solutions will present and demonstrate Exensio Aurora, a new AI-first, highly scalable architecture for its Exensio analytics solution. Exensio Aurora is purpose-built to handle semiconductor manufacturing data at petabyte scale and to securely deploy agentic AI across manufacturing operations and the supply chain.
The announcement addresses a structural shift in the industry. Advancement in 3D architecture, advanced packaging and heterogeneous integration are driving innovation and revenue growth in the semiconductor industry, dissolving the boundary between front-end and back-end and dispersing production globally. The direct impact of this kind of complexity is the massive increase in the magnitude of the manufacturing data semiconductor companies must deal with.
As the senior executive from a leading fabless company observed at the PDF Solutions users conference in December 2025, “our engineering and manufacturing data has grown 600% since 2022.” That is the operating reality across the industry, and it exposes a hard truth: Semiconductor manufacturing generates enormous volumes of data, yet typically, based on the analytics tools currently in use, less than 5% of it is analyzed.
To quote a recent article from an industry analyst: “Beneath this growth lies a structural shift. Manufacturing complexity is rising faster than the industry’s ability to manage it. As architectures move deeper into 3D, production disperses globally, and product cycles compress, scale alone is no longer a differentiator. Operational coherence is.” (Kalar Rajendiran, SemiWiki Feb 10 2026).
At SEMICON West 2025, John Kibarian, PDF Solutions’ CEO, remarked that the semiconductor industry thrives on innovation, which is fueled by collaboration. But the nature of this collaboration is changing. The growing technology trend towards 3D and hybrid packaging is creating a larger and more complex global supply chain. He explained that the ability to leverage AI at all levels to drive operational efficiency is required. However, this is predicated on the ability to apply AI at scale, supported by a platform able to align and analyze data from across the ecosystem.
Commonly used Business Intelligence (BI) systems cannot adequately process semiconductor manufacturing data that is both extremely long and extremely wide. Furthermore, general-purpose cloud data platforms lack three essentials for this domain: integration with manufacturing equipment and processes, an industry-grounded semantic model, and the ability to orchestrate actions across business applications and the supply chain.
Meeting this moment requires a fundamentally different kind of platform; one designed from the ground up to handle semiconductor data, connected directly to manufacturing processes and equipment, able to scale AI agents across the enterprise, and open enough to support genuine ecosystem collaboration across the chiplet supply chain. A platform developed on the specific evolving requirements of semiconductor companies mobilizing the latest technology available. As Said Akar, PDF Solutions head of development, mentioned in a recent video, “every few years there is a new combination of business issues that need solving and new emerging technology components to solve them.” A leading industry platform must closely align with the evolution of the needs of the industry, while being able to incorporate the latest technology available.
Weighing in-memory processing limits of conventional BI tools, lack of semiconductor manufacturing relevance in general-purpose cloud data platforms, and at the urging of several of its customers, PDF Solutions chose to invest in a new kind of analytics architecture, called Exensio Aurora, to power the PDF Solutions platform.
Aurora leverages PDF Solutions’ extensive experience with the semiconductor context: the specific structure, scale, and semantic of manufacturing data, and is engineered to enable agentic AI across both the enterprise and the manufacturing supply chain. Built as a cloud-first solution, Exensio Aurora also supports on premise deployment and delivers the speed and scale required for both online and offline applications.
AI is the foundational guiding principle the Exensio Aurora architecture is built around: from the way semiconductor industry content is included in model development and AI training, to the way users interact with the application, and into the workflows and guardrails ensuring the AI can be scaled and trusted.
The goal is not just to deliver faster analytics. The goal is to transform the role of analytics for engineering and operations staff. To move from running the same analytics constrained by the available data to providing a new kind of experience centered on investigating larger questions related to the dynamic of the underlying process.
Exensio Aurora is the foundation for a platform that integrates online and offline data and control, amplifies the value locked in legacy manufacturing systems, and extends internal processes outward into AI-driven supply-chain orchestration. In an era defined by heterogeneous integration and exploding data complexity, it is designed to do what conventional tools cannot: turn all of the data, all of the time, into decisions, at the scale the industry now demands.
To experience Exensio Aurora first-hand, to meet with the team that developed it and to hear from early adopters of some of its capability register and attend PDF Solutions CONNECT October 15–16 in San Francisco.
Visit PDF Solutions CONNECT 2026 conference website to learn more about the agenda, speakers, location, logistics and registration.
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