MathWorks has released the new R2026a for MATLAB and Simulink, expanding AI capabilities applicable to the embedded system development process. This update focuses on accelerating development while maintaining the accuracy of design and verification.

MathWorks announced on April 28 the release of R2026a and stated that it has introduced Copilot capabilities applicable across model-based design and software verification. This enables the management of the development flow, from requirements definition to design, code writing, and verification, as a single system.

Simulink Copilot, one of the core features, provides design guidance based on user models, the organization's development processes, and official documentation. Engineers can quickly understand model structures and explore necessary blocks, and receive root cause analysis and solution suggestions when issues arise. These capabilities are utilized to reduce repetitive work and shorten error correction time during the design phase.

In the software verification area, Polyspace Copilot and 'Polyspace as you code' features have been added. Developers can identify rule violations or potential defects during the code writing phase and interpret and correct issues based on static analysis results. This contributes to reducing overall development costs and time by identifying errors in the early stages of development.

This release also includes an integrated analysis environment. The new PolySpace desktop application enables configuration and results management within a single interface and extends the testing and verification process through dynamic analysis capabilities and custom checkers. This allows for consistent quality management across all stages of development, testing, and verification.

In addition, various updates have been added, including educational content creation tools, FMU generation capabilities for model exchange, improved Python integration, and wireless network analysis features. MathWorks explained that it is expanding its technology to enhance overall engineering efficiency and reproducibility by integrating AI into existing development environments while linking with agentic workflows.