It was a pleasure meeting Haysam Telib at the ESTECO Users’ Meeting India 2025 in Pune. As the CEO & CTO of Optimad Engineering—acquired by ESTECO in August 2024—Haysam now plays a pivotal role in driving ESTECO’s portfolio expansion into Explainable AI and Deep Learning. In our conversation, he shared insightful perspectives on the evolving role of AI in engineering. Check out his thoughts on the future of AI here.
DailyCADCAM: What is the meaning of explainable AI in the context of ESTECO technology?
Haysam Telib: Explainable AI are models that are inspectable and constructed with building blocks that can be interpreted and even questioned by the end-user. Once principles and their limitations are well understood, users will gain confidence in the models and will start using them confidently. ESTECO’s mission is to empower engineers with this kind of technology.
DailyCADCAM: How does ESTECO’s AI-Data Driven Modeling technology shorten product development cycles?
Haysam Telib: Honestly, it depends very much on the use case, but when it comes to very competitive landscapes, where engineers chase after top-notch performances, AI can be a game changer. In order to push performances further and further, engineers require high quality data from the very beginning to make informed decisions. But such kind of data is typically also very costly, think of Large Eddy Simulation (LES) simulations in aerodynamics or crash simulations or even experimental data. Through ESTECO’s AI Data Driven modelling, engineers will exploit all available high quality data, company-wide, even from past development cycles. This will boost their work especially in the first phase of the product development cycle and reduce risks of unexpected behaviour further downstream. In other words, it will allow for front-loading and to allocate valuable time for final iterations and tuning that require significant human effort.
DailyCADCAM: How does Reduced Order Models (ROM) integrate with ESTECO digital engineering software solutions?
Haysam Telib: When talking about AI, everyone has predictions on his or her mind. While this is the feature that everyone wants to test, it takes a much more articulated journey to make it a scalable and robust solution over time in a complex system like an automotive OEM. This is why here in ESTECO we’re developing a Machine Learning Operations (MLOps) platform for engineers. For example through modeFRONTIER you can standardize the simulation process to assure the quality of generated data. And you can use best-in-class algorithms to explore the design space while controlling costs. Finally through VOLTA you get governance and traceability, which is pivotal for AI systems that are based on internal data.
DailyCADCAM: How does the automation of AI/ML training simulation workflows benefit engineers?
Haysam Telib: Automation is a key enabler for a simulation-driven design process and it is no different for a data-driven process. We must all acknowledge that data is dynamic, since our engineers want to stay on the edge with the simulation capabilities or simply validate designs that are generated by an AI-assisted process. And when new data is generated, you want to make your AI agents aware of that. And the best way to achieve that is through automation together with traceability.
At the end of day, there will be an orchestrated synergy between simulation technology and AI, the former being responsible for generating data with added-value and the latter for providing fast responses.
DailyCADCAM: In what ways does ESTECO’s technology provide governance and democratize the use of AI/ML models for predictive modeling?
Haysam Telib: As I mentioned before, governance is pivotal for AI systems that are based on the customers’ data. Especially in engineering, where fractions of a percent may matter. To have a sharp model with small errors, it is mandatory to ensure the quality of the data used for training. ESTECO’s technology stack provides the governance tools to ensure that quality. Primary by providing full traceability of models and users who generated the data. Only once the system is perfectly governed, it can be deployed safely to all stakeholders that need the model. And again we provide our customers with fine-grained collaboration capability, by distinguishing roles, like AI model creators and designers who consume the model to accelerate their work.
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About
Haysam Telib
CEO & CTO,
Optimad
After graduating in Mechanical Engineering from Technical University of Munich, he obtained his PhD in fluid mechanics from Politecnico di Torino and acoustics from Ecole Central de Lyon for his dissertation on Aeroacoustic optimization of aeronautical propellers. During his Postdoc at University of Bordeaux and Politecnico di Torino he was appointed inviting researcher at Boeing to work on acceleration techniques for aeroelastic optimization. Since 2010 he holds the position of CEO & CTO at Optimad.
After the acquisition of OPTIMAD, Haysam is supervising ESTECO’s portfolio expansion in the field of Explainable AI and Deep Learning.
Thank you, Haysam Telib, for sharing your valuable insights with DailyCADCAM. If readers have any questions for ESTECO, feel free to reach out to us at sachin@dailycadcam.com.
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