Automate engineering processes at scale

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  pSeven Desktop  v2025.06
Desktop application for design exploration, predictive modeling, CAD/CAE integration and automation.

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  pSeven Enterprise  v2025.07
Low-code cloud-native platform to automate engineering processes at scale.

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  Design Exploration
Solve complex engineering problems with state-of-the-art tools for DoE, UQ and design optimization.

  Predictive Modeling
Predict response values for new designs, accelerate complex simulations and capture knowledge from vast amounts of data.

  Process Integration
Integrate all your CAD/CAE packages into a single workflow, explore virtual prototype behavior and eliminate repetitive tasks with automation.

  SmartSelection
Automatic choosing of appropriate and the most effective DoE, UQ, optimization and predictive modeling algorithms.

  Low-code automation
Capture complex engineering processes and define execution logic thanks to a powerful workflow engine and low-code approach.

  Collaborative engineering
Improve collaboration within and between the teams with simultaneous multi-user access and co-authoring of the workflows in real-time.

  Server-side execution
Run many resource-consuming simulation workflows simultaneously without interruption with a built-in resource manager.

  Workflows as web apps
Share simulation methodologies with other users across and outside the organization in a from of DIY workflow-powered web apps.

  Integration with PLM / SPDM
Boost PLM / SPDM systems with enhanced simulation workflow execution.

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pSevenCompanyPublicationsIntegrating simulation systems with pSeven to solve pumping outfit optimization problems

Integrating simulation systems with pSeven to solve pumping outfit optimization problems

Authors:

Sergey Sumarokov, General Director, CALS-center

Journal / Event:

DATADVANCE User Conference 2021

Keywords: DUC2021, Energy, Oil and Gas, Energy

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Contacts

France, 31100 Toulouse, Av. du Général de Croutte 42

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info@pseven.io

Integrating simulation systems with pSeven to solve pumping outfit optimization problems

Authors:

Journal / Event:

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