Complex engineering problems demand rigorous planning, systematic execution, and the coordinated use of specialized tools to deliver safe, reliable, and validated products under tight development schedules.

Driven by recent advances in artificial intelligence and continued platform evolution at d3VIEW, we have integrated enterprise-grade Agentic Engineering Workflows (AEW) into the d3VIEW environment. These workflows are powered by autonomous and semi-autonomous engineering agents with access to more than 1,500 domain-specific tools. The agents execute multi-step engineering tasks through natural-language driven orchestration, enabling repeatable and auditable workflows.

The current Agentic Engineering Solutions (AES) library supports a broad range of engineering activities, including machine-learning model development, full-vehicle design-of-experiments (DOE) execution and optimization, simulation model debugging and validation, ontology-based knowledge representation and reasoning, and material model calibration. Users may deploy pre-configured AES components, extend existing agents, or construct custom agents using a visual, whiteboard-based workflow authoring approach.

The d3VIEW AES library is expected to expand significantly in 2026, enabling engineers and domain specialists to execute increasingly complex, agent-guided engineering workflows that improve traceability, reduce iteration cycles, and accelerate product development from concept through validation.