{"id":109877,"date":"2026-03-06T11:48:58","date_gmt":"2026-03-06T11:48:58","guid":{"rendered":"https:\/\/www.simscale.com\/?page_id=109877"},"modified":"2026-03-09T10:17:10","modified_gmt":"2026-03-09T10:17:10","slug":"physics-ai","status":"publish","type":"page","link":"https:\/\/www.simscale.com\/product\/physics-ai\/","title":{"rendered":"Physics AI"},"content":{"rendered":"\n<style data-wp-block-html=\"css\">\n\/* Removing Padding from Vertical Differentiator Section *\/\n.hw-verticalDifferentiator--section {\n    padding: 0px !important;\n}\n.hw-verticalDifferentiator {\n    padding: 0px !important;\n}\n<\/style>\n\n\n\n<div class=\"gb-element-a1ba63a4\" style=\"--inline-bg-image: url(https:\/\/frontend-assets.simscale.com\/media\/2025\/10\/product-background-svg.svg)\">\n<div class=\"gb-element-3e3f3809\">\n<div class=\"gb-element-d62f41e5\">\n<div class=\"gb-element-b775d3a3\">\n<h1 class=\"gb-text gb-text-39d788ad\">Physics AI<\/h1>\n\n\n\n<h2 class=\"gb-text gb-text-344ac21f\">Explore thousands of design points in seconds<\/h2>\n\n\n\n<p class=\"gb-text gb-text-d3a21d04\">Physics AI predicts real physical behavior in seconds using models trained on high-fidelity simulation data, enabling instant design exploration without sacrificing engineering trust.<\/p>\n\n\n\n<div class=\"gb-element-ac7061bc\">\n<div>\n<a class=\"gb-text gb-text-80819dc1\" href=\"\/signup\/\">Try SimScale<\/a>\n<\/div>\n\n\n\n<div class=\"gb-element-3a131f83\">\n<a class=\"gb-text gb-text-4949f631\" href=\"\/request-demo\/\">Book a Demo<\/a>\n<\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-69caf842\">\n<div>\n<img loading=\"lazy\" decoding=\"async\" width=\"109\" height=\"33\" class=\"gb-media-24b6e220\" alt=\"G2 Ratings\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2025\/09\/g2crowd_icon_updated.svg\" title=\"g2crowd_icon_updated\"\/>\n<\/div>\n\n\n\n<div>\n<img loading=\"lazy\" decoding=\"async\" width=\"119\" height=\"47\" class=\"gb-media-2a5022e5\" alt=\"Capterra Rating\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2025\/08\/Capterra.svg\" title=\"Capterra\"\/>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-865bfb3b\">\n<img loading=\"lazy\" decoding=\"async\" width=\"619\" height=\"407\" class=\"gb-media-7029e06d\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/explore-thousands-design-points-physics-ai.webp\" alt=\"Explore thousands of design points in seconds with Physics AI\" title=\"Explore thousands of design points in seconds with Physics AI\" srcset=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/explore-thousands-design-points-physics-ai.webp 619w, https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/explore-thousands-design-points-physics-ai-300x197.webp 300w, https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/explore-thousands-design-points-physics-ai-515x339.webp 515w\" sizes=\"auto, (max-width: 619px) 100vw, 619px\" \/>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-a9018355\">\n<style>\n\/* Logobar Scrolling *\/\n@keyframes marquee {\n    from { transform: translateX(0); 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johnson logo\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2022\/10\/johnson-johnson.svg\" title=\"johnson-johnson\"\/>\n<\/div>\n\n\n\n<div class=\"gb-element-fec480b4\">\n<img loading=\"lazy\" decoding=\"async\" width=\"118\" height=\"18\" class=\"gb-media-1dccf39d\" alt=\"Nobel logo\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2024\/11\/nobel_automotive_logo.svg\" title=\"nobel_automotive_logo\"\/>\n<\/div>\n\n\n\n<div class=\"gb-element-38a5ee22\">\n<img loading=\"lazy\" decoding=\"async\" width=\"60\" height=\"25\" class=\"gb-media-ca8050d3\" alt=\"bucher municipal logo\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2023\/09\/bucher_municipal_logo.svg\" title=\"bucher_municipal_logo\"\/>\n<\/div>\n\n\n\n<div class=\"gb-element-9b2c5221\">\n<img loading=\"lazy\" decoding=\"async\" width=\"84\" height=\"17\" class=\"gb-media-90228fca\" alt=\"b\u00fchler logo\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2023\/09\/buhler_logo.svg\" title=\"buhler_logo\"\/>\n<\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-b6c723fd\">\n<div class=\"gb-element-ef963417\">\n<img loading=\"lazy\" decoding=\"async\" width=\"146\" height=\"11\" class=\"gb-media-79933292\" alt=\"zaha hadid architects logo\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2022\/10\/zaha-hadid.svg\" title=\"zaha-hadid\"\/>\n<\/div>\n\n\n\n<div class=\"gb-element-961ca424\">\n<img loading=\"lazy\" decoding=\"async\" width=\"62\" height=\"14\" class=\"gb-media-2729a311\" alt=\"aecom logo\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2022\/10\/aecom.svg\" title=\"aecom\"\/>\n<\/div>\n\n\n\n<div class=\"gb-element-2776504c\">\n<img loading=\"lazy\" decoding=\"async\" width=\"101\" height=\"16\" class=\"gb-media-3d60b71b\" alt=\"mitsubishi logo\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2022\/10\/mitsubishi.svg\" title=\"mitsubishi\"\/>\n<\/div>\n\n\n\n<div class=\"gb-element-fcbc52f2\">\n<img loading=\"lazy\" decoding=\"async\" width=\"106\" height=\"17\" class=\"gb-media-c2dc50e8\" alt=\"\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2024\/09\/toshiba_logo_grey.svg\" title=\"toshiba_logo_grey\"\/>\n<\/div>\n\n\n\n<div class=\"gb-element-faae7759\">\n<img loading=\"lazy\" decoding=\"async\" width=\"90\" height=\"19\" class=\"gb-media-899cbca7\" alt=\"Magna Logo\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2022\/11\/Magna-logo.svg\" title=\"Magna-logo\"\/>\n<\/div>\n\n\n\n<div class=\"gb-element-fdc98680\">\n<img loading=\"lazy\" decoding=\"async\" width=\"70\" height=\"25\" class=\"gb-media-ae6cbbc8\" alt=\"thornton tomasetti logo\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2022\/10\/thornton-tomasetti.svg\" title=\"thornton-tomasetti\"\/>\n<\/div>\n\n\n\n<div class=\"gb-element-d301ed7f\">\n<img loading=\"lazy\" decoding=\"async\" width=\"90\" height=\"26\" class=\"gb-media-66f7e7e5\" alt=\"sweco logo\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2022\/10\/sweco.svg\" title=\"sweco\"\/>\n<\/div>\n\n\n\n<div class=\"gb-element-ee3d4ff5\">\n<img loading=\"lazy\" decoding=\"async\" width=\"113\" height=\"25\" class=\"gb-media-94eb7d70\" alt=\"aqseptence group logo\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2022\/10\/aqseptence.svg\" title=\"aqseptence\"\/>\n<\/div>\n\n\n\n<div class=\"gb-element-3df2c6ea\">\n<img loading=\"lazy\" decoding=\"async\" width=\"130\" height=\"24\" class=\"gb-media-daec3388\" alt=\"johnson &amp; johnson logo\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2022\/10\/johnson-johnson.svg\" title=\"johnson-johnson\"\/>\n<\/div>\n\n\n\n<div class=\"gb-element-b13c47d7\">\n<img loading=\"lazy\" decoding=\"async\" width=\"118\" height=\"18\" class=\"gb-media-e865b3ec\" alt=\"Nobel logo\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2024\/11\/nobel_automotive_logo.svg\" title=\"nobel_automotive_logo\"\/>\n<\/div>\n\n\n\n<div class=\"gb-element-ffd6c09d\">\n<img loading=\"lazy\" decoding=\"async\" width=\"60\" height=\"25\" class=\"gb-media-389a4ad8\" alt=\"bucher municipal logo\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2023\/09\/bucher_municipal_logo.svg\" title=\"bucher_municipal_logo\"\/>\n<\/div>\n\n\n\n<div class=\"gb-element-0f425cb8\">\n<img loading=\"lazy\" decoding=\"async\" width=\"84\" height=\"17\" class=\"gb-media-0babf610\" alt=\"b\u00fchler logo\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2023\/09\/buhler_logo.svg\" title=\"buhler_logo\"\/>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-ca241487\">\n<div class=\"gb-element-3bbef0ea\">\n<div class=\"gb-element-24cb668e\">\n<div>\n<h3 class=\"gb-text gb-text-949770cc\">Instant Prediction. Grounded in Physics.<\/h3>\n\n\n\n<p class=\"gb-text gb-text-2a2ec004\">Physics AI models learn from large volumes of high-fidelity simulation data to predict physical behavior in seconds. Engineers can evaluate design performance instantly without waiting for full simulation runs. Results remain grounded in validated physics models, enabling engineering speed without sacrificing credibility.<\/p>\n<\/div>\n\n\n\n<div class=\"gb-element-b3ba4cd1\">\n<img loading=\"lazy\" decoding=\"async\" width=\"563\" height=\"315\" class=\"gb-media-d9a439bb\" alt=\"Instant Prediction. Grounded in Physics.\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/instant-prediction-grounded-in-physics.webp\" title=\"Instant Prediction. Grounded in Physics.\" srcset=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/instant-prediction-grounded-in-physics.webp 563w, https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/instant-prediction-grounded-in-physics-300x168.webp 300w, https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/instant-prediction-grounded-in-physics-515x288.webp 515w\" sizes=\"auto, (max-width: 563px) 100vw, 563px\" \/>\n<\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-e189a812\">\n<div class=\"gb-element-0a2dd0f6\">\n<img loading=\"lazy\" decoding=\"async\" width=\"560\" height=\"315\" class=\"gb-media-07ffa323\" alt=\"Turn Past Engineering Data Into Future Decisions\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/turn-past-engineering-data-future-decisions.webp\" title=\"Turn Past Engineering Data Into Future Decisions\" srcset=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/turn-past-engineering-data-future-decisions.webp 560w, https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/turn-past-engineering-data-future-decisions-300x169.webp 300w, https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/turn-past-engineering-data-future-decisions-515x290.webp 515w\" sizes=\"auto, (max-width: 560px) 100vw, 560px\" \/>\n<\/div>\n\n\n\n<div class=\"gb-element-5f66e6dc\">\n<h3 class=\"gb-text gb-text-3611d4c2\">Turn Past Engineering Data Into Future Decisions<\/h3>\n\n\n\n<p class=\"gb-text gb-text-f6c19d23\">SimScale\u2019s cloud-native architecture turns every simulation run into a potential model training asset, building a proprietary IP dataset that fuels your AI strategy and gets smarter with every project. Engineering teams move from running isolated simulations to building reusable prediction capabilities.<\/p>\n<\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-ebe5cff2\">\n<div>\n<h3 class=\"gb-text gb-text-387ae3f4\">Hybrid AI models with engineering confidence<\/h3>\n\n\n\n<p class=\"gb-text gb-text-8fdd7b4a\">Physics AI doesn\u2019t replace numerical solvers. It works alongside them. Explore variants instantly with AI predictions, then validate final candidates using full-fidelity CFD, FEA, thermal, or multi-physics solvers \u2014 all on the same platform. This hybrid approach delivers the speed of AI with the rigor of physics-based simulation.<\/p>\n<\/div>\n\n\n\n<div class=\"gb-element-8a930dd8\">\n<img loading=\"lazy\" decoding=\"async\" width=\"560\" height=\"343\" class=\"gb-media-a3075f39\" alt=\"Hybrid AI models with engineering confidence\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/hybrid-ai-models-engineering-confidence.webp\" title=\"Hybrid AI models with engineering confidence\" srcset=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/hybrid-ai-models-engineering-confidence.webp 560w, https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/hybrid-ai-models-engineering-confidence-300x184.webp 300w, https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/hybrid-ai-models-engineering-confidence-515x315.webp 515w\" sizes=\"auto, (max-width: 560px) 100vw, 560px\" \/>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-86c317a6\">\n<div class=\"gb-element-388f5b8c\">\n<div class=\"gb-element-4251263c\">\n<h2 class=\"gb-text gb-text-381e9eb9\"><strong>Stop Waiting. Start Optimizing. <\/strong>&nbsp;When simulation feedback takes hours, innovation slows and competitive advantage slips. Physics AI delivers instant physics insight so engineers can optimize faster.<\/h2>\n\n\n\n<p class=\"gb-text gb-text-51862197\">How Physics AI Works in Practice<\/p>\n<\/div>\n\n\n\n<style>\n.step-dot-cell { position:relative; }\n\n\/* Dot colours *\/\n.gb-element-aa100001 .gb-element-ab100001 { background:#F6F6F6 !important; border:1px solid #E0E0E0; }\n.gb-element-aa100002 .gb-element-ab100002 { background:#EEEEEE !important; }\n.gb-element-aa100003 .gb-element-ab100003 { background:#E5E5E5 !important; }\n.gb-element-aa100004 .gb-element-ab100004 { background:#999999 !important; }\n\n\/* Tiny connector above dot (matches the segment colour arriving from above) *\/\n.step-dot-cell:not(.step-first)::before {\n  content:\"\"; position:absolute;\n  top:0; height:6px;\n  left:50%; transform:translateX(-50%);\n  width:5px; z-index:0;\n}\n.gb-element-aa100002::before { background:#EEEEEE; }\n.gb-element-aa100003::before { background:#E5E5E5; }\n.gb-element-aa100004::before { background:#999999; }\n\n\/* Line segments below each dot \u2014 gradient matches dot colour at top to next dot colour at bottom *\/\n.step-dot-cell:not(.step-last)::after {\n  content:\"\"; position:absolute;\n  top:calc(6px + 10px); bottom:-60px;\n  left:50%; transform:translateX(-50%);\n  width:5px; z-index:0;\n}\n.gb-element-aa100001::after { background:linear-gradient(to bottom,#F6F6F6,#EEEEEE); }\n.gb-element-aa100002::after { background:linear-gradient(to bottom,#EEEEEE,#E5E5E5); }\n.gb-element-aa100003::after { background:linear-gradient(to bottom,#E5E5E5,#999999); }\n\n@media (max-width:767px) {\n  .step-dot-cell { display:flex !important; }\n}\n<\/style>\n\n\n\n<div>\n<div class=\"gb-element-387ddbbd\">\n<div class=\"gb-element-aa100001 step-dot-cell step-first\">\n<div class=\"gb-element-ab100001\"><\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-0dae3944\">\n<div class=\"gb-element-3a8634d5\">\n<h3 class=\"gb-text gb-text-0bfa1517\">1. Generate Data at Scale<\/h3>\n\n\n\n<p class=\"gb-text gb-text-bc174c0d\">Reliable AI models require high-fidelity data to accurately capture the design space. With SimScale, engineers can leverage existing historical simulation data or generate new datasets using cloud-native solvers. By running hundreds of design variants in parallel, teams can rapidly build the large, structured datasets needed for robust model training that faithfully represent the underlying physics of the system.<\/p>\n<\/div>\n\n\n\n<div class=\"gb-element-0f6f5d93 gb-element-2b869e45\">\n<img loading=\"lazy\" decoding=\"async\" width=\"561\" height=\"320\" class=\"gb-media-730d5320\" alt=\"Generate Data at Scale\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/generate-data-at-scale.webp\" title=\"Generate Data at Scale\" srcset=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/generate-data-at-scale.webp 561w, https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/generate-data-at-scale-300x171.webp 300w, https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/generate-data-at-scale-515x294.webp 515w\" sizes=\"auto, (max-width: 561px) 100vw, 561px\" \/>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-13afbe75\">\n<div class=\"gb-element-aa100002 step-dot-cell step-middle\">\n<div class=\"gb-element-ab100002\"><\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-d74f7dcd\">\n<div class=\"gb-element-b42e3c46\">\n<h3 class=\"gb-text gb-text-1b14e48e\">2. Train Physics AI Models<\/h3>\n\n\n\n<p class=\"gb-text gb-text-6de61370\">Physics AI models learn the relationships between design parameters and physical performance from high-fidelity simulation results. SimScale leverages datasets from over 1,000,000 public simulation projects to train models that capture complex multi-physics behavior. These models can instantly predict performance across thousands of new design variations, enabling engineers to explore large design spaces far faster than traditional simulation.<\/p>\n<\/div>\n\n\n\n<div class=\"gb-element-b3a58fff gb-element-734af884\">\n<img loading=\"lazy\" decoding=\"async\" width=\"560\" height=\"315\" class=\"gb-media-0b33fa80\" alt=\"Train Physics AI models\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/train-physics-ai-models.webp\" title=\"Train Physics AI models\" srcset=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/train-physics-ai-models.webp 560w, https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/train-physics-ai-models-300x169.webp 300w, https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/train-physics-ai-models-515x290.webp 515w\" sizes=\"auto, (max-width: 560px) 100vw, 560px\" \/>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-11085856\">\n<div class=\"gb-element-aa100003 step-dot-cell step-middle\">\n<div class=\"gb-element-ab100003\"><\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-c9bda63e\">\n<div class=\"gb-element-b42e3c46\">\n<h3 class=\"gb-text gb-text-85a5c43b\">3. Hybrid AI\u2013Physics Architecture<\/h3>\n\n\n\n<p class=\"gb-text gb-text-b7b2e8a8\">SimScale uniquely integrates traditional simulation and Physics AI side-by-side within a single unified platform. Because both analysis types use the same configuration and setup process, you can switch between them effortlessly. This allows your team to use Physics AI for near-instant design exploration and then instantly run a high-fidelity CFD or FEA simulation to validate your final design candidates.<\/p>\n<\/div>\n\n\n\n<div class=\"gb-element-d0b4c72a gb-element-734af884\">\n<img loading=\"lazy\" decoding=\"async\" width=\"560\" height=\"315\" class=\"gb-media-64133767\" alt=\"Hybrid AI simulation\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/hybrid-ai-simulation-ezgif.com-gif-to-webp-converter.webp\" srcset=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/hybrid-ai-simulation-ezgif.com-gif-to-webp-converter.webp 560w, https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/hybrid-ai-simulation-ezgif.com-gif-to-webp-converter-300x169.webp 300w, https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/hybrid-ai-simulation-ezgif.com-gif-to-webp-converter-515x290.webp 515w\" sizes=\"auto, (max-width: 560px) 100vw, 560px\" \/>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-7411a487\">\n<div class=\"gb-element-aa100004 step-dot-cell step-last\">\n<div class=\"gb-element-ab100004\"><\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-f1e7e2ac\">\n<div class=\"gb-element-8b717cc8\">\n<h3 class=\"gb-text gb-text-e00dd194\">4. Instant Inference<\/h3>\n\n\n\n<p class=\"gb-text gb-text-d759804b\">Run inferences across your entire engineering ecosystem\u2014interactively in your browser, through integrated CAD software, or via fully autonomous optimization cycles. Whether you are using the SimScale UI or orchestrating work through autonomous AI agents and APIs, every model is versioned, monitored, and published within SimScale\u2019s enterprise-grade simulation process and data management (SPDM) solution.<\/p>\n<\/div>\n\n\n\n<div class=\"gb-element-c42ff781 gb-element-a6e7110d\">\n<img loading=\"lazy\" decoding=\"async\" width=\"560\" height=\"315\" class=\"gb-media-b8cb9688\" alt=\"Instant Inference\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/instant-inference.webp\" title=\"Instant Inference\" srcset=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/instant-inference.webp 560w, https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/instant-inference-300x169.webp 300w, https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/instant-inference-515x290.webp 515w\" sizes=\"auto, (max-width: 560px) 100vw, 560px\" \/>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-f6cbdfe1\">\n<div class=\"gb-element-394e24b3\">\n<h2 class=\"gb-text gb-text-c39d558b\">Built on Industry-Leading AI Frameworks<\/h2>\n<\/div>\n\n\n\n<div class=\"gb-element-059406e6\">\n<div class=\"gb-element-b4e4f767\">\n<img loading=\"lazy\" decoding=\"async\" width=\"282\" height=\"53\" class=\"gb-media-7fa8d208\" alt=\"nVidia logo\" title=\"nVidia Logo\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/nvidia-logo.svg\"\/>\n<\/div>\n\n\n\n<div class=\"gb-element-5ca3942b\">\n<img loading=\"lazy\" decoding=\"async\" width=\"796\" height=\"86\" class=\"gb-media-506aec67\" alt=\"navasto logo\" title=\"NAVASTO_logo_no_background\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2023\/08\/NAVASTO_logo_no_background.png\" srcset=\"https:\/\/frontend-assets.simscale.com\/media\/2023\/08\/NAVASTO_logo_no_background.png 796w, https:\/\/frontend-assets.simscale.com\/media\/2023\/08\/NAVASTO_logo_no_background-300x32.png 300w, https:\/\/frontend-assets.simscale.com\/media\/2023\/08\/NAVASTO_logo_no_background-768x83.png 768w\" sizes=\"auto, (max-width: 796px) 100vw, 796px\" \/>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-4064fb1d\">\n<div class=\"gb-element-653e3685\">\n<h2 class=\"gb-text gb-text-e6724894\">Where Physics AI Delivers Measurable Impact<\/h2>\n<\/div>\n\n\n\n<div class=\"gb-element-6590e181\">\n<div class=\"gb-element-3bc665ac\">\n<div class=\"gb-element-43c09255\">\n<img loading=\"lazy\" decoding=\"async\" width=\"978\" height=\"623\" class=\"gb-media-81c115f9\" alt=\"NPD Acceleration\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2025\/11\/npd.webp\" title=\"npd\" srcset=\"https:\/\/frontend-assets.simscale.com\/media\/2025\/11\/npd.webp 978w, https:\/\/frontend-assets.simscale.com\/media\/2025\/11\/npd-300x191.webp 300w, https:\/\/frontend-assets.simscale.com\/media\/2025\/11\/npd-768x489.webp 768w\" sizes=\"auto, (max-width: 978px) 100vw, 978px\" \/>\n<\/div>\n\n\n\n<div class=\"gb-element-5305ad5c\">\n<h3 class=\"gb-text gb-text-777c5e5a\">NPD acceleration<\/h3>\n\n\n\n<p class=\"gb-text gb-text-9f390622\">By enabling engineers to explore thousands of virtual design options instantly, Physics AI eliminates the &#8220;wait-and-test&#8221; bottlenecks that often delay product launches. Instead, teams can rapidly iterate through diverse design candidates and support portfolio diversification without increasing overheads. Engineering teams move faster from concept to launch.<\/p>\n\n\n\n<a class=\"gb-text gb-text-abc7cc0d\" href=\"https:\/\/www.simscale.com\/use-cases\/npd-acceleration\/\">Learn More<\/a>\n<\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-64868d0c\">\n<div>\n<h3 class=\"gb-text gb-text-08a8c35a\">RFQ Automation<\/h3>\n\n\n\n<p class=\"gb-text gb-text-4d8dbcba\">Respond to complex engineering RFQs with faster technical insight. Physics AI evaluates design feasibility and performance instantly, helping teams produce stronger proposals with greater confidence. By replacing slow, specialist-dependent simulation cycles with instant AI inference, you can submit more accurate, data-backed proposals in a fraction of the time, protecting margins and increasing win rates.<\/p>\n\n\n\n<a class=\"gb-text gb-text-1968e150\" href=\"https:\/\/www.simscale.com\/use-cases\/rfq-automation\/\">Learn More<\/a>\n<\/div>\n\n\n\n<div class=\"gb-element-fcd60d57\">\n<img loading=\"lazy\" decoding=\"async\" width=\"978\" height=\"623\" class=\"gb-media-e48e3cb7\" alt=\"RFQ Automation\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2025\/11\/rfq-1.webp\" srcset=\"https:\/\/frontend-assets.simscale.com\/media\/2025\/11\/rfq-1.webp 978w, https:\/\/frontend-assets.simscale.com\/media\/2025\/11\/rfq-1-300x191.webp 300w, https:\/\/frontend-assets.simscale.com\/media\/2025\/11\/rfq-1-768x489.webp 768w\" sizes=\"auto, (max-width: 978px) 100vw, 978px\" \/>\n<\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-9cfdf000\">\n<div class=\"gb-element-118e5768\">\n<img loading=\"lazy\" decoding=\"async\" width=\"978\" height=\"623\" class=\"gb-media-15464ba9\" alt=\"Real Time Digital Twins\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2025\/11\/digital-twins.webp\" srcset=\"https:\/\/frontend-assets.simscale.com\/media\/2025\/11\/digital-twins.webp 978w, https:\/\/frontend-assets.simscale.com\/media\/2025\/11\/digital-twins-300x191.webp 300w, https:\/\/frontend-assets.simscale.com\/media\/2025\/11\/digital-twins-768x489.webp 768w\" sizes=\"auto, (max-width: 978px) 100vw, 978px\" \/>\n<\/div>\n\n\n\n<div class=\"gb-element-c740fab9\">\n<h3 class=\"gb-text gb-text-5a9bb547\">Real-Time Digital Twins<\/h3>\n\n\n\n<p class=\"gb-text gb-text-68a76b62\">Physics AI enables real-time prediction of physical system behavior under changing operating conditions. Through SimScale\u2019s robust API, AI-powered surrogate models integrate directly into your operational data streams and simulation process loops.. This allows teams to optimize operation, anticipate performance issues, and support continuous engineering insight across the product lifecycle.<\/p>\n\n\n\n<a class=\"gb-text gb-text-16768ed9\" href=\"#pricingtable\">Learn More<\/a>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"gb-element-f5bbb12e\">\n<div class=\"gb-element-5864c4e7\">\n<div class=\"gb-element-d8987ef2\">\n<h2 class=\"gb-text gb-text-5c7e4fcb\">Trusted by 800,000+ engineers worldwide<\/h2>\n<\/div>\n\n\n\n<div class=\"gb-element-6f9d2662\">\n<div>\n<h3 class=\"gb-text gb-text-bc0d4730\">RLE INTERNATIONAL Group Simulates\u2028Vehicle Aerodynamics in Seconds<\/h3>\n\n\n\n<p class=\"gb-text gb-text-7fca2f4b\">RLE International transformed its automotive design process by integrating Physics AI to deliver reliable aerodynamic insights in seconds rather than hours. By leveraging SimScale\u2019s cloud-native infrastructure, RLE built an end-to-end workflow that generates massive training datasets in parallel, cutting computation costs by 45% compared to traditional methods.<\/p>\n\n\n\n<a class=\"gb-text gb-text-50e497b9\" href=\"https:\/\/www.simscale.com\/customers\/rle-international-group-simulates-vehicle-aerodynamics-in-seconds\/\">Learn More<\/a>\n<\/div>\n\n\n\n<div class=\"gb-element-3162ef9d\">\n<img loading=\"lazy\" decoding=\"async\" width=\"560\" height=\"324\" class=\"gb-media-3ac6621a\" alt=\"RLE Customer Success Simulation\" src=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/rle-customer-success-simulation.webp\" title=\"RLE Customer Success Simulation\" srcset=\"https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/rle-customer-success-simulation.webp 560w, https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/rle-customer-success-simulation-300x174.webp 300w, https:\/\/frontend-assets.simscale.com\/media\/2026\/03\/rle-customer-success-simulation-515x298.webp 515w\" sizes=\"auto, (max-width: 560px) 100vw, 560px\" \/>\n<\/div>\n<\/div>\n\n\n\n<div class=\"gb-query-08be7a91\"><div class=\"gb-looper-e0bbdf2a\">\n<div class=\"gb-loop-item gb-loop-item-469e475d post-103794 page type-page status-publish has-post-thumbnail hentry\">\n<div class=\"gb-element-0da2babd\" style=\"--inline-bg-image: url(https:\/\/frontend-assets.simscale.com\/media\/2025\/06\/siemens_success_story_cover_image_1x.webp)\"><\/div>\n\n\n\n<div class=\"gb-element-44aaad48\">\n<h3 class=\"gb-text gb-text-d00f8bf3\"><a href=\"https:\/\/www.simscale.com\/customers\/siemens-energy-3d-printed-product-optimization\/\">Siemens Energy 3D-Printed Product Optimization<\/a><\/h3>\n<\/div>\n<\/div>\n\n<div class=\"gb-loop-item gb-loop-item-469e475d post-108671 page type-page status-publish has-post-thumbnail hentry\">\n<div class=\"gb-element-0da2babd\" style=\"--inline-bg-image: url(https:\/\/frontend-assets.simscale.com\/media\/2025\/11\/Kemper-Cover-Image.webp)\"><\/div>\n\n\n\n<div class=\"gb-element-44aaad48\">\n<h3 class=\"gb-text gb-text-d00f8bf3\"><a href=\"https:\/\/www.simscale.com\/customers\/kemper-driving-progress-in-drinking-water-hygiene\/\">Kemper &#8211; Driving Progress in Drinking Water Hygiene<\/a><\/h3>\n<\/div>\n<\/div>\n\n<div class=\"gb-loop-item gb-loop-item-469e475d post-84109 page type-page status-publish has-post-thumbnail hentry\">\n<div class=\"gb-element-0da2babd\" style=\"--inline-bg-image: url(https:\/\/frontend-assets.simscale.com\/media\/2023\/11\/20231114-cs-tecnalia-Featured.jpg)\"><\/div>\n\n\n\n<div class=\"gb-element-44aaad48\">\n<h3 class=\"gb-text gb-text-d00f8bf3\"><a href=\"https:\/\/www.simscale.com\/customers\/tecnalia-leverages-cfd-cloud-simulation\/\">TECNALIA Leverages CFD and Cloud Simulation for UAV Design &#038; Development<\/a><\/h3>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n<div class=\"gb-element-4960c472\">\n<a class=\"gb-text gb-text-86fd7fbd\" href=\"\/customers\/\">See All Case Studies<\/a>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<div>\n<div class=\"gb-element-8405afe3\">\n<div class=\"gb-element-9c036482\">\n<h2 class=\"gb-text gb-text-0b760fc3\">Time is no longer the enemy. It\u2019s your advantage.<\/h2>\n\n\n\n<p class=\"gb-text gb-text-6d721e30\">Explore Physics AI with SimScale<\/p>\n\n\n\n<div class=\"gb-element-92ea2574\">\n<div>\n<a class=\"gb-text gb-text-1a9a803a\" href=\"\/signup\/\">Start Simulating Now<\/a>\n<\/div>\n\n\n\n<div class=\"gb-element-f05e812e\">\n<a class=\"gb-text gb-text-0cd7c50e\" href=\"\/request-demo\/\">Speak to an Expert<\/a>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Physics AI Explore thousands of design points in seconds Physics AI predicts real physical behavior in seconds using...","protected":false},"author":195,"featured_media":100893,"parent":9,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"templates\/template-hw-blank.php","meta":{"_acf_changed":false,"_crdt_document":"","inline_featured_image":false,"footnotes":""},"class_list":["post-109877","page","type-page","status-publish","has-post-thumbnail","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.simscale.com\/wp-json\/wp\/v2\/pages\/109877","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.simscale.com\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.simscale.com\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.simscale.com\/wp-json\/wp\/v2\/users\/195"}],"replies":[{"embeddable":true,"href":"https:\/\/www.simscale.com\/wp-json\/wp\/v2\/comments?post=109877"}],"version-history":[{"count":0,"href":"https:\/\/www.simscale.com\/wp-json\/wp\/v2\/pages\/109877\/revisions"}],"up":[{"embeddable":true,"href":"https:\/\/www.simscale.com\/wp-json\/wp\/v2\/pages\/9"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.simscale.com\/wp-json\/wp\/v2\/media\/100893"}],"wp:attachment":[{"href":"https:\/\/www.simscale.com\/wp-json\/wp\/v2\/media?parent=109877"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}