Accelerate your product development with scalable engineering automation
Automate CAD/CAE tools, streamline design exploration, and empower cross-team collaboration to deliver better products, faster.
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3rd of December | pSeven SAS and Qarnot to host a webinar on collaborative engineering using sustainable HPC in the cloud. Learn morenavigate_next
Automate CAD/CAE tools, streamline design exploration, and empower cross-team collaboration to deliver better products, faster.
Learn more navigate_next
Desktop application for design optimization and process integration (PIDO)
Design Exploration
Explore various design alternatives and easily find optimal solutions with Design of Experiments and Design Optimization strategies.
Automatic choosing of algorithms
Predictive Modeling
Predict response values for new designs, accelerate complex simulations and capture knowledge from vast amounts of data.
Automatic choosing of techniques
Process Integration
Automate complex product development processes by integrating all your CAD/CAE software into a single workflow and defining its logic.
Web-native low-code platform for engineering automation at enterprise scale
Low‑code automation
Capture even the most complex engineering processes, define its logic and collect, analyze and reuse engineering data thanks to powerful workflow engine and low-code approach.
Collaborative engineering
Collaborate easily with your teammates, suppliers or partners: private and shared workspaces, simultaneous co-authoring of workflows and analysis of results in the cloud.
Workflow-powered web apps
Share simulation methodologies with other users across and outside the organization in a from of DIY workflow-powered web apps.
This article introduces the work of the Center of Advanced Die Engineering and Technology (G-CADET), a comprehensive manufacturing research center at Gifu University, highlighting its efforts to realize the automatic search for molding process conditions and autonomous operation by leveraging big data accumulated through optimization process.
Find out how predictive modelling techniques and engineering solutions are shaping the future of automotive acoustics. Explore a web-based application that automates the evaluation of loudspeaker positioning within vehicle interiors. This application enables quick design iterations, reduces manual effort and assists non-experts in making informed audio design decisions.
pSeven Enterprise transforms complex simulation business processes into automated multidisciplinary workflows. This transformation formalizes processes, eliminates data transfer errors and accelerates simulation. Furthermore, automated simulation workflows enable parametric, multidisciplinary design optimization.
The research article from our partner in Korea, RaonX. This study proposes a method for developing high-fidelity finite element (FE) models based on multiobjective optimization using pSeven's capabilities. Three 10-kW-class wind turbine blades were manufactured and tested. The modal parameter changes were measured and the modal analysis results were compared with the experimental results, proving the high-fidelity quality of the model-building approach.
This article describes how the features presented above can be applied to real-world examples of wing design.
pSeven Enterprise allowed to automate the simulation processes inside different departments and after that link the dependencies between those simulations in one master workflow to create a full-scale digital prototype of a jet engine.
Repetitive manual operations during compressor map cunstruction such as building geometry models, mesh generation, post-processing of the results and data exchange between different software were automated in pSeven Enterprise.
Another Use Case for Formula Student. In this project, a group of students from the Formula Student optimized the attachment points of the rear suspension of the new version of their racing bolide using pSeven Desktop.
pSeven Desktop based project that allowed create an automated workflow for parametric analysis and optimization of car suspension dampers in order to ensure passenger vibration comfort and smooth vehicle behavior on the road.
This article introduces the work of the Center of Advanced Die Engineering and Technology (G-CADET), a comprehensive manufacturing research center at Gifu University, highlighting its efforts to realize the automatic search for molding process conditions and autonomous operation by leveraging big data accumulated through optimization process.
Find out how predictive modelling techniques and engineering solutions are shaping the future of automotive acoustics. Explore a web-based application that automates the evaluation of loudspeaker positioning within vehicle interiors. This application enables quick design iterations, reduces manual effort and assists non-experts in making informed audio design decisions.
pSeven Enterprise transforms complex simulation business processes into automated multidisciplinary workflows. This transformation formalizes processes, eliminates data transfer errors and accelerates simulation. Furthermore, automated simulation workflows enable parametric, multidisciplinary design optimization.
The research article from our partner in Korea, RaonX. This study proposes a method for developing high-fidelity finite element (FE) models based on multiobjective optimization using pSeven's capabilities. Three 10-kW-class wind turbine blades were manufactured and tested. The modal parameter changes were measured and the modal analysis results were compared with the experimental results, proving the high-fidelity quality of the model-building approach.
This article describes how the features presented above can be applied to real-world examples of wing design.
pSeven Enterprise allowed to automate the simulation processes inside different departments and after that link the dependencies between those simulations in one master workflow to create a full-scale digital prototype of a jet engine.
Repetitive manual operations during compressor map cunstruction such as building geometry models, mesh generation, post-processing of the results and data exchange between different software were automated in pSeven Enterprise.
Another Use Case for Formula Student. In this project, a group of students from the Formula Student optimized the attachment points of the rear suspension of the new version of their racing bolide using pSeven Desktop.
pSeven Desktop based project that allowed create an automated workflow for parametric analysis and optimization of car suspension dampers in order to ensure passenger vibration comfort and smooth vehicle behavior on the road.
This collaboration delivers a seamless integration between Aras Innovator and pSeven Enterprise, empowering engineering organizations to accelerate innovation, eliminate silos, and bring high-value products to market faster.
pSeven SAS, provider of advanced software solutions for design process automation and optimization, and Qarnot, pioneer in European HPC cloud computing, are pleased to announce a new technology partnership.
pSeven SAS, a leading provider of advanced data analytics and optimization solutions, is excited to announce a strategic partnership with Digital House Group, a privileged partner in consulting engineering, digital innovation and digital transformation.
How can engineering teams overcome common bottlenecks in the car suspension design cycle by leveraging automated simulation workflows and scalable cloud computing resources? We will demonstrate at the webinar.
We are excited to announce that pSeven will participate in the upcoming NAFEMS themed day “Contributions of numerical simulation to the development and use of carbon-free energy sources”, which will take place on November 13, 2025, in Paris. This event highlights the critical role of digital tools in decarbonizing energy sources and optimizing complex engineering processes.
The event will focus on future solutions for manufacturing, including digital twins, AI, materials development, quantum computing, and supply chain.
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phone +33 (0) 5 82-95-59-68
mail_outline info@pseven.io
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