Emerson expands AI code generation tool across test software suite
Emerson is rolling out its Nigel AI technology across the NI test software portfolio, adding prompt-based code generation to LabVIEW+ Suite. The expansion, expected later this year, targets aerospace, semiconductor and transportation companies developing products under strict reliability and safety requirements.
Nigel launched last year as a test-optimized AI system built to work within the constraints of engineering test environments. The expansion extends it across FlexLogger, InstrumentStudio, TestStand and SystemLink, providing guidance from initial development through validation and deployment.
In internal testing, engineers reduced test development and troubleshooting cycles from days or hours to minutes using Nigel.
How the platform works
The NI platform combines modular hardware, open software and a shared data foundation. At the hardware level, it delivers low size, weight and power consumption while supporting diverse signals, precise timing and high-performance data movement.
The software layer connects operating environments and computing technologies, allowing test workflows to incorporate AI over time. A shared data foundation simplifies how teams capture, manage and reuse measurement data across sites.
This integration matters for product developers because it means you can add AI capabilities to existing workflows without rebuilding your infrastructure.
Who's using it
During the NI Connect conference in Fort Worth this week, companies including NVIDIA, Alstom, Valeo, Zap Energy and Cyth Systems described using NI test and measurement technologies to accelerate development and validation of next-generation products.
Ritu Favre, president of Emerson's test and measurement business, said the platform's strength lies in how its hardware, software, data and ecosystem work together. "As AI reshapes product development, it's this adaptability that allows our AI-ready platform to stand out," Favre said.
If your team develops test code, you may find value in exploring how AI coding courses or generative code resources can help you understand these capabilities more deeply.
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