The upgraded CodeFusion Studio 2.0 simplifies how developers design, test and deploy AI on embedded systems.
Updated
January 8, 2026 6:34 PM
Illustration of CodeFusion Studio™ 2.0 showing AI, code and chip icons. PHOTO: ANALOG DEVICES, INC.
Analog Devices (ADI), a global semiconductor company, launched CodeFusion Studio™ 2.0 on November 3, 2025. The new version of its open-source development platform is designed to make it easier and faster for developers to build AI-powered embedded systems that run on ADI’s processors and microcontrollers.
“The next era of embedded intelligence requires removing friction from AI development”, said Rob Oshana, Senior Vice President of the Software and Digital Platforms group at ADI. “CodeFusion Studio 2.0 transforms the developer experience by unifying fragmented AI workflows into a seamless process, empowering developers to leverage the full potential of ADI's cutting-edge products with ease so they can focus on innovating and accelerating time to market”.
The upgraded platform introduces new tools for hardware abstraction, AI integration and automation. These help developers move more easily from early design to deployment.
CodeFusion Studio 2.0 enables complete AI workflows, allowing teams to use their own models and deploy them on everything from low-power edge devices to advanced digital signal processors (DSPs).
Built on Microsoft Visual Studio Code, the new CodeFusion Studio offers built-in checks for model compatibility, along with performance testing and optimization tools that help reduce development time. Building on these capabilities, a new modular framework based on Zephyr OS lets developers test and monitor how AI and machine learning models perform in real time. This gives clearer insight into how each part of a model behaves during operation and helps fine-tune performance across different hardware setups.
Additionally, the CodeFusion Studio System Planner has also been redesigned to handle more device types and complex, multi-core applications. With new built-in diagnostic and debugging features — like integrated memory analysis and visual error tracking — developers can now troubleshoot problems faster and keep their systems running more efficiently.
This launch marks a deeper pivot for ADI. Long known for high-precision analog chips and converters, the company is expanding its edge-AI and software capabilities to enable what it calls Physical Intelligence — systems that can perceive, reason, and act locally.
“Companies that deliver physically aware AI solutions are poised to transform industries and create new, industry-leading opportunities. That's why we're creating an ecosystem that enables developers to optimize, deploy and evaluate AI models seamlessly on ADI hardware, even without physical access to a board”, said Paul Golding, Vice President of Edge AI and Robotics at ADI. “CodeFusion Studio 2.0 is just one step we're taking to deliver Physical Intelligence to our customers, ultimately enabling them to create systems that perceive, reason and act locally, all within the constraints of real-world physics”.
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As airports grow more complex, the real innovation lies in making their systems simpler, faster, and easier to act on
Updated
March 24, 2026 5:55 PM
An airplane parked at Josep Tarradellas Barcelona-El Prat Airport. PHOTO: UNSPLASH
Airports are some of the most complex systems in the world. Every day, they manage thousands of flights, passengers, crew schedules, gates and ground operations—all moving at the same time. But much of this still runs on older software that doesn’t connect well, making simple decisions harder than they need to be.
This is the gap companies like AirportLabs are trying to address. Instead of relying on multiple disconnected systems, their approach brings airport operations into one cloud-based platform. The goal is straightforward: take scattered data and turn it into something teams can actually use in real time.
In practice, this means combining core systems like flight databases, resource management and display systems into a single interface. When everything is connected, airport staff can respond faster—whether it’s adjusting gate assignments, managing delays, or coordinating ground crews. Rather than reacting late, decisions can be made as situations unfold.
Another shift is how this technology is built. Traditional airport systems often require heavy on-site infrastructure and long deployment timelines. In contrast, cloud-based platforms remove much of that complexity. Updates are faster, systems are easier to scale and teams spend less time maintaining servers and more time improving operations.
What stands out is the speed of adoption. Instead of multi-year rollouts, newer systems can be implemented in weeks, allowing airports to see improvements much sooner.
At a broader level, this reflects a familiar pattern seen across industries. As operations become more data-heavy, the advantage shifts to those who can simplify complexity. In aviation, that doesn’t just mean better technology—it means making the entire system easier to run.