HBK, VI-grade, and MOVEdot Formed AI Partnership
The companies have integrated AI agents to streamline automotive simulation and testing workflows.
Updated on Sept. 21, 2026 in Automotive — General
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HBK and VI-grade have partnered with MOVEdot to incorporate AI-powered engineering agents into their automotive testing and simulation platforms. This collaboration aims to accelerate engineering decision-making by enabling AI to reason across complex datasets.
Why it matters
The integration allows engineering teams to connect disparate data from files, databases, and APIs, helping them synthesize information faster during the product development cycle.
The new platform integrates with existing simulation software and MATLAB/Simulink environments. It supports data connectivity across diverse sources including databases, lakehouses, and various API-driven architectures.
The players
HBK
HBK is a global provider of test and measurement solutions for the automotive industry.
VI-grade
VI-grade specializes in simulation and virtual testing software for vehicle development.
MOVEdot
MOVEdot is a technology firm that develops AI agents tailored for engineering and technical data reasoning.
The details
The MOVEdot AI agents are designed to reason across test results, simulation outcomes, and technical documentation simultaneously. By operating within existing engineering frameworks, the platform bridges gaps between physical testing data and digital simulation results.
Timeline
The partnership between the three companies was officially announced on September 21, 2026.
Roadmap
This partnership reflects a broader industry pivot toward incorporating generative and analytical AI agents into traditional automotive R&D cycles. As simulation software becomes more complex, automakers are increasingly relying on these automated tools to manage the massive influx of data generated during virtual testing.
Automotive engineers and R&D teams can expect more seamless data integration, which may reduce the time spent manually cross-referencing simulation and physical test results. This shift aims to streamline the development cycle for vehicle systems, potentially accelerating the time-to-market for new models.
The takeaway
Automotive manufacturers are shifting toward AI-integrated workflows to handle increasingly fragmented engineering data. Adopting these reasoning agents can help teams identify patterns across simulation results and testing databases that might otherwise remain obscured.
Further reading
Explore more industry trends on the Automotive — General page.
Source note: This article includes information reported by Engineerlive.
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