Digital Engineering

Data-Driven, Connected, and Automated Engineering

Uncover new insights from data sources, connected toolsets, and seamless collaboration. Adopt the latest use cases, govern data standards, and connect systems of analysis in a unified experience. Automate pipelines of data and computing across globally distributed value chains to fast track new product innovations.


Shared resource access and collaboration between teams and organizations

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Data Management

Data enrichment, governance, and analytics to accelerate R&D velocity and quality

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Computational Pipelines

Automate R&D processes with configurable compute and data flows

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Digital Engineering COLLABORATION

Connected Simulation Collaboration and
Data Sharing

Connect distributed teams and value-chain partners to collaborate on modern product R&D. Unify silos of analysis across the organization with shared access and context on computing and data resources. Improve data quality and process efficiency in complex multidisciplinary projects by collaborating directly on product models.

Knowledge Management

Your Data Accessible In-Context
Where and When You Need It

Unify data with workloads in the cloud for greater productivity, collaboration, and efficiency by organizing data by jobs or by file attributes. Easily tag, filter, and search files to streamline data sharing among workspace users and multi-job workflows. Manage storage costs and job integrity organization-wide with policy-driven retention and deletion of files, jobs, and directories. Seamlessly connect data sources to deliver secure and controlled access at the organization, project, and user levels.


End-to-End Workflow &
Pipeline Automation

Accelerate complex, multi-stage workflows and computational pipelines with event-driven automations. Rescale’s Job Lifecycle Automation enables R&D users to orchestrate workflows programmatically, with fine-grained controls to optimize jobs for parallel execution and license utilization. Bi-directional file system integration automates uploading and downloading of input and output files and Workflow Builder to connect a chain of jobs.


Gateway to Modern
AI-Driven R&D

Accelerate R&D discovery and new product development by integrating the latest AI/ML capabilities. Explore larger design spaces and increasing complexity of data and computing requirements to bring new innovations to market faster. Leverage Rescale’s AI-enhanced workload optimization and automated computational pipelines to efficiently train and validate ML models. Empower engineers with the latest technologies for digital twins, physics-informed neural networks, and generative design.


Open Platform for
Connected Innovation

Rescale is open and extensible to unify workflows, build any custom environments, and seamlessly integrate thousands of tools for R&D. Enable a digital-thread approach by integrating existing platforms including product life cycle management (PLM), and connect to your data wherever it lives including data warehouses/lakes or network file systems. Rescale Compass Services are available to help you connect your systems of insight and accelerate workflows on Rescale.

Customer spotlight

Exponent Expands HPC Capabilities With Rescale to Drive the Future Of Computational Engineering

Exponent provides a wide variety of engineering and scientific consulting services to the world’s largest innovators. With growth in the number of clients, projects, and consultants requiring HPC, Exponent selected Rescale to provide a scalable and easy-to-uses solution to drive project efficiency and improve client results. With the use of Rescale Exponent was able to achieve:

  • 10x acceleration of engineering computing solve speeds
  • 10x increase in simulation fidelity to meet growing job complexity

Related Resources

Computational Pipeline for Automating Multi-Step Simulation R&D Workflows

Demo Overview Computational pipelines on Rescale streamline R&D by automating complex computing workflows, reducing manual steps and accelerating time to insight. With computational pipelines Individual tasks can be standardized and automated, improving engineering speed, accuracy, and overall productivity. This capability can be applied to a variety of industries and tools – as an example this…