Using digital twin and AI mapping technology, the agent tracks change relationships automatically and assesses the impact of a change on vehicle models, ECUs, test items and supplier parts. It links regulatory and process milestones so that change risk can be managed visually.
Version and configuration are transparent across the workflow, and the impact scope of a change is identified precisely.
Change reviews are more than 80% faster, removing the manual work of tracing related items.
Automatically links regulatory requirements and SOP milestones so that changes comply with industry rules and process standards.
Real configuration changes are mapped to the virtual model, which stays updated and continuously tracked.
A large language model serves as the reasoning core, tuned on automotive R&D and testing corpora to support requirement parsing, root cause reasoning and code generation.
Brings together ZD simulation knowledge, historical fault cases and diagnostic experience with retrieval-augmented generation, so output matches real engineering contexts.
Supports local and private-cloud deployment so R&D data never leaves the company, meeting OEM data security and compliance requirements.
Agent output connects directly to test execution, simulation scheduling and ticketing systems, so results flow automatically and are tracked to closure.
Requirement, software version, hardware selection and BOM changes are captured automatically, the affected vehicle models, ECUs, test items and supplier parts are mapped precisely, and change reviews become more than 80% faster.
Real configuration changes are mapped to the virtual model, which is kept updated and tracked, making version and configuration transparent across the workflow.
ZD Technology · AI agents for vehicle R&D and testing