Rescale Data Intelligence: Unlocking the Next Generation of Engineering Productivity

The announcement of Rescale Data Intelligence marks a significant expansion of Rescale’s digital engineering platform. This new set of integrated capabilities automatically captures contextual knowledge, accelerates discovery, and deploys AI where simulation work happens.

This announcement represents a reimagining of how engineering organizations harness the modeling and simulation data they generate. While simulation teams generate more data than ever, that data remains largely inaccessible, trapped in disconnected systems, missing critical context, and requiring significant effort to find it when it’s needed. Today, engineers and scientists spend upwards of 40% of their time managing data instead of innovating. Teams unknowingly duplicate 30%+ of their simulation work to reproduce data. Critical insights remain siloed, and tracing engineering decisions becomes nearly impossible after six months.

Rescale Data Intelligence provides a unified data fabric, agentic automation, and AI Physics methods delivered in a single integrated platform, transforming simulation data from passive records to active, actionable data.

Why Digital Engineering Deserves a New Approach

The data challenge is massive. Of the zettabytes of data generated globally just in the manufacturing sector alone, only 5% will be effectively utilized due to fragmented data silos. Yet 87% of IT and data leaders agree that data management is a top priority to drive innovation. And the urgency couldn’t be clearer. Leading analysts point out that manufacturers lack full product data visibility, whereas rising product development complexity, AI demands, and shifting regulations require a unified solution. According to Gartner, CIOs must urgently adopt digital threads to connect lifecycle data, enable digital engineering, and build an AI-ready foundation.

Traditional enterprise data platforms face a fundamental challenge: implementation timelines stretching 9+ months struggle to keep up with rapidly evolving technologies and methodologies, while adoption rates often remain low years into deployments. These systems are designed as systems of record—capturing information after work is complete. Continuous simulation workflows, however, generate critical context about modeling assumptions, convergence behavior, and engineering insights that can be lost before reaching centralized repositories.

As organizations appoint new data and AI leaders to address these challenges, a critical understanding has emerged. Solving the data intelligence challenge requires both top-down architecture decisions that establish standards and data foundations, as well as bottom-up engineering adoption that integrates into daily workflows without disrupting how work gets done.

Rescale Data Intelligence approaches this challenge by providing fit-for-purpose technology architecture and data foundations designed for how AI-driven engineering work actually happens. Organizations need platforms that embrace a flexible, portfolio approach rather than forcing teams into rigid architectures or requiring them to rebuild models from scratch. Across industries, 70% of AI’s potential value is found in core business functions such as R&D and innovation. That’s why the Rescale platform focuses on these areas while maintaining the flexibility to adapt as technologies and methodologies advance.

Breakthrough Capabilities That Transform Engineering Workflows

Rescale delivers transformation through three capabilities designed to support workflows where critical engineering work happens, from performing simulations to product decision-making.

Build R&D Data Foundations with a Unified Data Fabric and AI Intelligence

First, Rescale Data Intelligence automatically captures contextual knowledge at the point of execution, not through post-processing or manual tagging, but as simulations run across any solver or hardware configuration.

Rescale Data Fabric syncs with external systems of record, creating a traceable digital thread that unifies information across product lifecycle management (PLM), simulation process and data management (SPDM), and cloud storage without requiring migration or replacement. Organizations gain a complete, queryable view of their simulation history—not just what was designed, but how it was analyzed and why decisions were made.

Rescale’s AI assistant transforms this foundation into actionable intelligence. Engineers ask questions in natural language and receive cross-disciplinary insights in seconds, with queries like “Show me all designs tested under the specified operating conditions where the selected performance metric exceeds the defined threshold.” The system surfaces domain-specific patterns that accelerate decision-making, and common queries can be templatized and shared across organizations.

Organizations implementing this approach see 70%+ reduction in data management time (from hours to minutes per week), 100% metadata capture compared to less than ~30% with manual processes, and 80% weekly active usage without training requirements.

Transform Systems of Record with a System of Action

With contextual knowledge automatically captured, Rescale Data Intelligence unlocks true agentic automation, deploying AI where simulation work happens, to transform passive data repositories into active systems that power engineering workflows. Through the integration of the Model Context Protocol (MCP) and Rescale Assistant, simulation agents can orchestrate complex multi-step analyses with human-in-the-loop checkpoints, automatically launching simulations when parameters change. These agents can also generate analysis reports with rich data visualizations that would typically require hours of manual effort. For organizations with centralized reporting requirements, results can be synced and validated with third-party systems like PLM, SPDM, and business analytics platforms. According to Boston Consulting Group research, AI and autonomous agents are estimated to accelerate time-to-market by 10-20% and lower R&D costs by up to 20%, highlighting a big potential difference between market leaders adopting these technologies and those who fall behind.

Applied AI Built on Simulation Data to Accelerate R&D Cycles

Advanced simulation and data intelligence come together to deliver Rescale’s third key platform capability: AI Physics methods that accelerate discovery by turning simulation datasets into deployable intelligence.

Rescale’s AI Physics operating system provides a complete stack and open ecosystem of tools to train, tune, validate, and publish surrogate models into a shared model hub accessible to simulation users, CAD designers, and product analysts. Engineers and scientists can develop and own their physics models and harness third-party model architectures like NVIDIA PhysicsNeMo without requiring data science expertise. The Rescale platform provides a scalable pipeline for continuously fine-tuning models as new simulation data becomes available.

An Integrated Platform, Not Another Isolated Tool

Rescale Data Intelligence represents a strategic platform expansion, not a standalone product. By unifying data capabilities with the world’s largest network of engineering applications and compute infrastructure, we’ve created something fundamentally different from traditional approaches that force organizations to manage separate systems for computing workloads and data management. Rescale supports flexible and interoperable deployment across any cloud provider to meet speed, cost, and compliance requirements.

Implementation takes days rather than months. Organizations go from first call to production data in under one week, compared to much longer deployment timelines for legacy systems. The platform requires zero training. Engineers continue working exactly as they do today while the system captures, organizes, and enriches their work automatically.

Powered By Comprehensive Platform Features

These capabilities are enabled by integrated platform features that work together to form Rescale’s data intelligence layer, automatically capturing context, enabling discovery, and orchestrating action across the engineering lifecycle.

Key Features Include:

• Automations Framework and Automated Metadata Extraction – Automatically extracts key parameters, results, and context from simulations across many popular commercial and open-source solvers, achieving complete data capture without manual intervention or data entry.
• Rescale Assistant – AI-powered natural language interface that enables engineers to search, analyze, and visualize simulation data across all projects with domain-specific intelligence and sub-3-second response times.
• AI-Driven Job Summaries – Generates automatic summaries for every simulation with key findings, anomaly detection, failed job diagnosis, and recommendations that make results immediately actionable for technical and non-technical stakeholders.
• System of Record Connectors – Integrates with engineering data platforms (e.g. PLM, SPDM, requirements management) and enterprise systems (e.g. data warehouse, document management, etc.) to import historical data, maintain bi-directional sync, and preserve existing system investments while unlocking greater context and insights.
• Smart Tagging & Custom Fields – AI-suggested metadata labels combined with admin-enforced custom fields ensure consistent data capture and standardization while learning organizational terminology and conventions.
• Workflow Builder – Visual designer for creating templatized multi-step workflows that automate complex design exploration, optimization studies, and AI training data preparation without requiring custom code.

Built for Everyday Engineering Workflows

Unlike traditional enterprise software that requires workflow changes and mandates adoption, Rescale Data Intelligence works with natural engineering processes and addresses the everyday tasks that consume engineers’ time. For IT and data management teams, the platform provides comprehensive administrative capabilities including AI-powered analytics for billing and resource optimization, policy-based control for automated data standards, and role-based permissions for security and budget allocation. Product and project leaders gain visibility into R&D productivity, data reuse patterns, and opportunities for workflow optimization, with analytics intelligence and cost-performance optimization across compute and data resources.

Use Cases to Deliver Immediate Value

• Data Enrichment – Automatically extract key findings from simulations to enrich metadata context, add structure, and provide centralized access with complete visibility on all historical analysis.
• Data Traceability – Search and understand the full context of simulation activities tied to product development decisions, including project objectives, product versions, findings, and team involvement.
• AI-Assisted Analysis – Query and visualize simulation results with built-in, domain-specific AI to explore data and uncover new insights using natural language prompts.
• Data Standardization – Gain visibility and ensure consistency in simulation data capture with automated reporting, policy-based controls, and reusable templates.
• Workflow Automation – Perform multi-step simulation analyses to explore large design spaces and evaluate multi-objective tradeoffs with automated orchestration.
• AI Training Pipelines – Prepare engineering data for AI model development by automating format conversion and staging in training environments for scalable training and inference.

The Next Chapter Begins Today

The next generation of engineering productivity demands intelligent platforms that capture contextual knowledge automatically, deploy AI where work happens, and accelerate discovery without disrupting how engineers actually work.

Product development and scientific discovery increasingly depend on the ability to harness data, automation, and computing to establish end-to-end digital threads for R&D. Organizations that move quickly in building these capabilities will capture competitive advantages through faster innovation cycles, higher engineering productivity, and more effective deployment of AI methods. Rescale Data Intelligence provides a practical path to these capabilities—one that works with existing investments, requires minimal implementation time, and delivers measurable returns within months rather than years. Industry pioneers shaping the future are harnessing their data to build their next innovations on Rescale.

Ready to transform how your organization captures, discovers, and acts on simulation data? Request a demo to see how Rescale Data Intelligence can deliver productivity gains and competitive advantages for your engineering teams.