Yet many engineering organizations are facing a critical roadblock – the right engineering data infrastructure to support trustworthy AI models. In a recent blog, Are Engineers Ready to Fully Embrace AI Models in Design and Analysis?, my colleague Ceyhun Sahin, Product Owner – nvision, explored this growing challenge - highlighting how fragmented workflows, poor data quality, and lack of structure can limit the real impact of AI in engineering.

Now, the next question is: How can engineers systematically create trustworthy, AI-ready data?

This is where Optimus, an automation and optimization tool by Noesis Solutions, plays a pivotal role.

From Engineering Automation to AI-Ready Data Generation

For more than 20 years, Optimus has been trusted by engineering teams worldwide as an automation and optimization platform for complex simulation workflows. Over time, it has continuously evolved - embracing advanced optimization methods, adaptive algorithms, and AI and machine learning technologies - all while staying deeply connected to existing engineering tools and processes, serving as a trustworthy data generation engine for AI-ready engineering workflows.

Optimus achieves this by acting as an integration layer that links diverse simulation tools through its interfaces and supports heterogeneous IT environments—including local clusters, HPC systems, and cloud submission. It orchestrates data exchange across these tools, ensuring consistent, reliable, and traceable results.

This creates the ideal foundation for building trustworthy AI models in design and analysis.

Adaptive DOE: Creating Smarter, AI-Ready Datasets

A key capability that enables AI readiness in Optimus is its Adaptive Design of Experiments (DOE) technology.

Unlike traditional DOE approaches that rely on fixed sampling plans, Adaptive DOE in Optimus continuously learns from simulation results and focuses computational effort where it matters most.

This enables:

• Better coverage of complex design spaces
• Faster identification of critical performance regions
• Reduced number of unnecessary simulation runs
• Higher-quality data for AI model training

The result is rich, meaningful datasets that capture real system behavior — ideal for machine learning and optimization.

Adaptive DOE ensures engineers generate not just more data, but the right data for AI.

Real-World Example: Turning Simulation into an AI Asset

Using Optimus, an engineering team runs an Adaptive DOE simulation campaign to explore thermal‑mechanical behavior across a wide design space. The resulting high‑quality dataset is seamlessly imported into nvision, where an AI surrogate model is trained to perform real‑time performance prediction based on the simulation results.

Within nvision, engineers can instantly explore new design variations, understand sensitivities, and evaluate what‑if scenarios without rerunning simulations, transforming simulation data into a reusable AI asset that accelerates design decisions across teams.

Trustworthy Data for Trustworthy AI Models

As highlighted in our earlier discussion on AI readiness, organizations that succeed with AI will be those that invest in data quality, structure, and intelligent generation strategies.

With Optimus, engineers can:

• Automate complex simulation workflows
• Intelligently explore design spaces
• Generate high-quality, AI-ready datasets
• Accelerate optimization and innovation

This unified approach reduces complexity, democratizes advanced technologies, and transforms simulation into a powerful driver for AI-powered engineering.

The Future of Engineering Is AI-Driven. Optimus Makes It Possible

AI in engineering is no longer a question of if, but how effectively it can be adopted. The journey starts with building trustworthy data. For over 20 years, Optimus has evolved alongside engineering challenges — and today, it stands as a powerful platform for engineering automation, simulation optimization, and AI-ready data generation.

By combining intelligent workflows, adaptive DOE, and seamless tool integration, Optimus empowers organizations to turn simulation into a strategic AI asset.

Let’s talk about how Optimus can you move from AI ambition to AI-ready execution.