See how Rescale turns AI from a tool into a scientific peer. In this demo, an agent takes on a lysozyme solvation study, moving beyond automating and troubleshooting GROMACS runs to diagnosing methodological confounds, debating experimental design against scientific intent, and configuring the right simulations so researchers can focus on the science.
Rescale presents a vision for a modernized simulation workflow built on three interconnected pillars: Compute, Data, and AI.
This NAFEMS World Congress 2025 session features Rescale’s VP of Product, Jacob Surber, alongside industry innovators from Rimac Technology, Subsea7, and Intelligent Energy, discussing the future of engineering simulation. Surber introduces Rescale’s transformative framework, integrating compute orchestration, data management, and AI to accelerate breakthroughs and overcome R&D bottlenecks in complex workflows, including a live demonstration…
AI-augmented simulation dramatically accelerates design evaluations using inference prediction. Rescale’s AI Physics gives aerospace engineers a complete solution to build, deploy, and tune custom AI models using existing simulation data to get rapid and high-accuracy results. Rescale’s full-stack security and compliance approach enables public sector agencies and contractors to harness unique capabilities in the cloud…
Revolutionize CAE with the Power of AI, Automation & Cloud Original Air Date: June 11th Discussion topics will include:
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…
Use Case Overview In this demo of Rescale Metadata Management, learn how to streamline the simulation processes and accelerate time-to-insight with automated data management. Automatically extract key performance indicators from simulation output files, enrich jobs with relevant context in tags, custom fields, and comments and then review an organized summary of results in the Rescale…
AI-Enabled Engineering Workflow Overview Learn more about AI Physics Powered by NVIDIA on Rescale Step 1 – Generate or Use Existing Simulation Data. Run Multiple CFD Simulations in Batch or Large Scale DOE, in this case with Siemens STAR-CCM+ to conduct a rear vehicle wing design study. Step 2 – Train Physics-Informed Surrogate Model by…
Rescale Metadata Management supports the templating and deploying of custom fields to workspaces. Custom fields allow for simulation data governance. Rescale supports automating the population of custom fields by executing python scripts as a post processing step for any simulation. The automation makes custom fields error free and saves simulation practitioners time and effort, increasing the productivity and reducing time-to-market.
Simulation engineers and engineering managers need to update simulations and iterate on product design several times before they are finalized, leading to large data sets. Searching for simulation data can become an overhead. Rescale allows tagging simulation data and searching for both file names and tags enabling organizations to reduce time and effort search for their data.
Use Case Demo Overview Engineering leaders need to enforce governance of simulation data in order to improve consistency of simulation results and compliance with industry regulation. Establishing governance while keeping engineering productivity high requires doing so in a way that doesn’t obstruct engineering and scientific computing. Simulation data governance on Rescale is seamless and flexible…
Products today require numerous teams collaborating on the design and testing of multiple components for a final product. Organizations use Rescale Metadata management to perform Model Based Collaboration resulting in faster handoffs and speedier decision making. By collaborating on models directly teams reduce the chance of errors creeping into the development process and improving product quality.
Demo video showcasing tagging and it’s application to improving data and decision traceability.
