Using multi-step AI reasoning, the agent consolidates project data, monitors key milestones, assesses project health, warns of emerging risks and recommends priority tasks, cutting reporting and coordination effort.
Weekly reports are generated automatically, cross-team coordination effort is reduced, and reporting workload for engineering managers drops significantly.
Monitors blockers, resource conflicts and supplier delays in real time, raising warnings early so that teams can act.
Analyses project health, identifies the critical path and recommends the tasks that matter most.
Brings together weekly reports, risks, milestones, resources and blockers, and the AI proposes actions.
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.
Financial monthly reports generated automatically: preparation time drops from 2 hours to 5 minutes, saving about 20 person-days a month, with over 99% data accuracy and reports delivered on time every time.
Brings together weekly reports, risks, milestones, resources and blockers, generates the weekly report automatically, warns of risks in real time and recommends the five things to push next week.
ZD Technology · AI agents for vehicle R&D and testing