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Engineering the Future Forward
Exploring the latest digital enginering use cases, industry trends, and Rescale platform innovations.
Blog
Exploring the latest digital enginering use cases, industry trends, and Rescale platform innovations.
What the biggest trends of 2026 mean for data and AI leaders and how Rescale…
A redesigned interface that introduces new capabilities for data intelligence, and agentic workflows, and AI…
AI agents can now handle routine simulation tasks while flagging key decision points that require…

Detect diverging and stalled simulations in real time, before they waste hours of compute. The Simulation Monitor automation runs alongside iterative solver jobs on Rescale, providing a live dashboard with residual plots, tabular data switching, and automated CSV exports without requiring an interactive workstation. It supports Ansys Fluent, STAR-CCM+, and CFX today, with a plugin-based…

Connect, find, and use external engineering data more easily on Rescale. Engineering data rarely lives in one place. Simulation inputs, reference documents, program files, and supporting context often sit across cloud object stores, SharePoint libraries, and other enterprise systems. That fragmentation slows teams down, especially when engineers need to find the right file quickly, attach…

Start training surrogate models faster with open-source AI Datasets now available in Rescale AI Physics. Engineers can now train models directly from the DrivAerML dataset, a subset of the high-fidelity open-source public dataset for automotive aerodynamics based on 500 parametrically morphed variants. Providing a great way to get started with AI Physics without having to…

Engineering teams can now put AI-first engineering into practice on Rescale — with new capabilities across agentic digital engineering, AI physics, and compute economics that streamline routine workflows, operationalize AI-assisted product development, and make smarter tradeoffs between speed, throughput, and cost.

Power complex and high-accuracy AI surrogate models for CFD and FEA with GeoTransolver model architecture. Now available in Rescale AI Physics as part of the NVIDIA PhysicsNeMo library, GeoTransolver is a geometry-aware transformer architecture that uses GALE attention to model relationships across complex 3D geometries and unstructured meshes. It is designed to generalize across changing…

Connect and interact with all your data in one place. Rescale now connects engineering data stored in AWS S3 and Azure Blob Storage directly to the Rescale Assistant through vectorized search. Once connected, engineers can ask natural language questions and receive fast, contextually grounded answers drawn from their organization’s own data, rather than relying only…

Presentation-ready reports in minutes vs. hours. Rescale’s Report Generator Agent eliminates the gap between raw results and structured reporting. Once a simulation study is complete, the agent takes the results data and automatically generates a report aligned to a customer’s own reporting templates, including findings, relevant charts, and recommendations.

Track and manage compute budgets in real-time. Rescale’s Budget Control Agent gives engineering and IT teams a proactive way to manage compute spend.

The Rescale AI Physics Local Inference App gives engineers a native desktop application for Windows, Mac, and Linux that works directly with AI models trained on the Rescale platform. Engineers can browse available models, install lightweight inference packages, and run predictions on their own hardware without an active cloud session.

How the next generation of cloud HPC is reshaping performance for digital twins and multi-physics simulation.

The 2026 NAFEMS Americas conference made it clear that the conversation on AI for digital engineering has shifted into high gear. A year ago, sessions on AI in simulation were largely exploratory. This year, a striking share of the program was devoted to AI deployment, what’s working, what’s not, and what comes next. AI applied…

Learn how simulation-native agents, a complete AI physics operating system, and novel cost controls help R&D teams move from manual workflows to automated agentic digital engineering.

McLaren Automotive is redefining the limits of performance by integrating AI physics and agentic AI into their design workflow.

What the biggest trends of 2026 mean for data and AI leaders and how Rescale is putting agentic engineering and AI physics to work in product development.

A redesigned interface that introduces new capabilities for data intelligence, and agentic workflows, and AI Physics on Rescale’s expanded platform.

Access Rescale’s Industry-leading Support 24/7 with new AI powered knowledge base and intelligent support assistant.

AI agents can now handle routine simulation tasks while flagging key decision points that require human judgment, shifting engineering time from logistical tasks to strategic innovation.

Amogy’s engineering team eliminated simulation bottlenecks and achieved 50% faster per-iteration solve times on Rescale, critical to accelerating ammonia-to-power innovation that supports decarbonization of heavy-duty power generation.

Engineers spend significant time aggregating and analyzing data instead of focusing on critical decision-making. Generative AI for modeling and simulation is changing that and unlocking new opportunities for innovation.

Rescale Data Intelligence establishes a unified data foundation that automatically captures simulation metadata, enables natural language search across all engineering systems, and powers AI-driven workflows, turning static legacy data into intelligent, actionable insights.