Cloud computing, simulation workflows, and AI physics for engineering and R&D teams.
Rescale is a digital engineering platform for engineering and R&D organizations. It combines cloud high-performance computing (HPC), modeling and simulation, agentic workflow automation, and AI physics in a shared environment.
Teams can run engineering workloads, coordinate multi-step simulations, and turn existing simulation results into datasets for AI surrogate models. These models provide predictions that approximate traditional simulations and support faster design iteration. The platform also provides resource policies, spending controls, and access management for organizations operating across teams and projects.
Run batch jobs and interactive engineering sessions on pre-configured CPU and GPU architectures. Multi-cloud orchestration and resource policies help allocate capacity according to performance and cost requirements.
Access a catalog of pre-installed commercial and open-source HPC and AI applications, with tools for deploying simulation software and managing licenses.
Build reusable workflows with templates, centralized job configuration, and dynamic hardware routing. Concurrent node limits, node-level failure controls, and failed-run resubmission support recovery when workflows encounter problems.
Use task-specific agents, multi-agent collaboration, and engineer-in-the-loop checkpoints. Connect cloud storage and enterprise systems, then ingest, index, and structure data into an engineering knowledge base.
Create datasets and train, evaluate, tune, deploy, version, and monitor surrogate models. Supported tools include Jupyter Notebook, NVIDIA Physics NeMo 2.0, and Rescale’s TwoStream transformer.
Set flexible or strict budgets by organization, project, or user. Spending analytics, forecasting, authentication controls, and event and data-transfer auditing support centralized administration.
Engineering and university research teams can use cloud bursting or migration to accommodate large simulation campaigns and changing compute demand.
Simulation teams can standardize multi-step processes in shared templates, reducing repeated configuration work across projects and supporting controlled execution.
Designers using Autodesk Alias or Blender can use CAD inference plugins to obtain AI-based physics approximations while changing geometry and exploring alternatives.
R&D teams with many similar historical simulations can train surrogate models to screen additional design candidates, reserving detailed simulation work for more complex conditions.
Rescale provides customized quotes. Packages combine a platform edition, product offerings, infrastructure options, and support. Infrastructure choices include on-demand priority, on-demand economy, and longer-term commitment plans.
Engineering workloads can be submitted through a graphical interface, command-line interface, or API. Elastic cloud workstations provide virtual desktops for visualization and interactive R&D work.
The pricing page lists Enterprise and Government editions. Government includes Enterprise capabilities with additional security and compliance provisions for federal agencies, public-sector organizations, and contractors.
Options include onboarding and implementation, ongoing technical support, dedicated customer success, hourly professional services, and embedded Rescale engineers for advanced use cases.
Os dados de tráfego são apenas para referência.
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