Engineering Simulation Platform · Now in Early Access

Engineering Simulation
in Minutes, Not Days

Physics-Intel accelerates thermal and airflow design decisions for electronic systems — transforming complex CFD workflows into guided, intelligent insight delivered in minutes, not days.

0×
Faster than Traditional FEA / CFD
< 2 min
CAD to Results, End-to-End
0%
Average Confidence Score
4
Target Industries
Interactive Product Demo

Auto-plays through all 12 steps of the pipeline · Use ◀ ▶ to navigate · Space to pause

The Pipeline

From Geometry to Insight in 8 Steps

A fully AI-guided workflow — no meshing expertise, no solver configuration, no post-processing required.

01
📦
STL / CAD Ingestion
Drop any electronic enclosure geometry. Physics-Intel ingests directly — no pre-processing, no format conversion required.
STL · CAD
02
🔬
Geometry Analysis
Automated mesh inspection and feature extraction. Identifies geometry complexity, thin walls, stress concentration zones, and physics type — no manual setup required.
Auto-Analysis
03
🎛️
Guided Setup
A conversational interface walks engineers through boundary conditions, loads, material properties, and constraints — with contextual guidance on every parameter.
Guided Setup
04
🧠
LLM Simulation Planning
GPT-4.1-mini generates a structured SimulationPlan — mesh density, solver configuration, refinement zones, and output field targets.
GPT-4.1-mini
05
⚡
MeshGraphNet Inference
NVIDIA PhysicsNeMo MeshGraphNet runs sub-second inference on the full 3D mesh graph — predicting velocity, temperature and pressure fields.
NVIDIA PhysicsNeMo
06
🎯
Confidence Gate
MC Dropout, PDE residual checks, and BC violation scoring determine result quality. Low-confidence runs auto-route to FEniCSx for high-fidelity validation.
FEniCSx · PINN
07
📋
Engineering Report
LLM interprets velocity, temperature and pressure fields into a scored thermal report — hotspot locations, overheating risk, and actionable recommendations.
Thermal Score
08
🔄
Continuous Learning
Every solve auto-registers a labeled training sample. The more you use it, the more accurate the surrogate models become — building toward a live digital twin simulation layer.
Digital Twin Ready
Under the Hood

Engineered for Speed, Accuracy & Physical Credibility

Physics-Intel integrates a carefully selected stack to deliver speed, accuracy, and physical credibility — across structural, thermal, and fluid simulation domains.

🟢
NVIDIA PhysicsNeMo
Surrogate Training Framework
The backbone of Physics-Intel's ML infrastructure. PhysicsNeMo provides pre-trained surrogate models, training pipelines, and physics-constrained learning tools for engineering simulation.
Core ML Platform
🕸️
MeshGraphNet
Graph Neural Network Solver
Represents computational meshes as graphs — nodes capture local physical state, edges encode neighborhood interactions. Delivers rapid surrogate predictions of velocity, temperature, and pressure fields across complex 3D geometries.
Graph Neural NetSub-second Inference
🔢
Physics-Informed Neural Networks
Constraint Layer
Physical laws — conservation of mass, momentum, and energy — are explicitly encoded into the learning process. Ensures predictions remain physically plausible and engineering-grade, even at speed.
PINNPhysics Constraints
🔬
FEniCSx
High-Fidelity Validation Solver
When the confidence gate flags low-certainty ML results, FEniCSx automatically runs a full finite element solve. Results are validated, marked Gold tier, and fed back to improve the surrogate model.
FEM FallbackGold Validation
🧠
GPT-4.1-mini
Intelligence Layer
Powers the geometry analysis, parameter advisor, simulation planning, and result interpretation layers. Provides engineering-grade guidance via a conversational interface — making expert-level CFD accessible to all engineers.
LLM Intelligence
☁️
Cloud-Native Infrastructure
Storage · API · Streaming
FastAPI backend with SSE streaming, Cloudflare R2 for geometry and result storage, Next.js 14 frontend with real-time 3D viewer. Built AI-first from the ground up for scalable collaboration and digital twin integration.
Cloud-NativeDigital Twin Ready
Simulation Domains

One Platform. Multiple Physics.

Physics-Intel handles the full range of engineering simulation workloads — from structural FEA to thermal management to fluid dynamics — with digital twin integration on the roadmap.

🔩
Structural FEA
Stress · Displacement · Fatigue · Safety Factor
Run stress analysis on mechanical components and assemblies in seconds. Identify failure zones, verify safety margins, and iterate on geometry — without waiting for a full FEM solve every time.
Static AnalysisFatigue & Life
🌡️
Thermal & Fluid (CFD)
Temperature · Velocity · Pressure · Heat Transfer
Predict airflow patterns and temperature distributions across complex geometries. Detect hotspots, optimise cooling configurations, and validate thermal margins — early in the design cycle.
Thermal ManagementAirflow
⚙️
Multiphysics
Coupled Thermal-Structural · Vibro-Acoustic · Fluid-Structure
Real-world problems rarely involve a single physics domain. Physics-Intel supports coupled simulations — thermal expansion driving structural stress, fluid pressure loading structures, and more.
Coupled SimulationFSI
🏭
Digital Twin (Roadmap)
Continuous Simulation · Live Asset Monitoring · Predictive Insight
Every simulation run builds a labeled dataset that improves the surrogate model over time. The vision: a persistent simulation layer that mirrors your physical asset — predicting behaviour before failures occur.
Self-ImprovingLive Insight

Works Across Industries

Automotive & EV Aerospace & Defense Electronics & Semiconductors Industrial Equipment Energy & Power Medical Devices
Key Benefits

Why Teams Choose Physics-Intel

Directly from our platform design principles — speed, credibility, and accessibility without compromise.

⚡
Simulation Cycles: Hours/Days → Minutes
ML surrogate inference runs in under a second. End-to-end — from geometry upload to engineering report — completes in under 2 minutes, for any physics domain.
🎯
Physically Grounded Results
PINNs encode conservation of mass, momentum, and energy. The confidence gate and FEniCSx fallback ensure physical credibility is never sacrificed for speed.
👩‍💻
No Simulation Specialist Required
The guided setup interface walks any engineer through boundary conditions, loads, and material properties. No manual meshing, no solver scripting, no post-processing expertise needed.
🏭
Digital Twin Ready
Cloud-native deployment with structured data storage. Infrastructure-ready for digital twin integration — Physics-Intel is designed to be the simulation intelligence layer.
🔄
Self-Improving with Every Run
Every simulation auto-registers a labeled training sample. The more you use it, the more accurate the surrogate models become for your specific enclosure geometries.
📊
Rapid Design Iteration
Run multiple geometry variants in minutes. Physics-Intel enables rapid side-by-side comparison across structural, thermal, or fluid scenarios — accelerating confident trade-offs between cost, performance, and reliability.
About Physics-Intel

Built for Industrial-Grade Engineering Simulation

Physics-Intel is an engineering simulation acceleration platform designed to help teams run structural, thermal, and fluid analyses on complex geometries — early, rapidly, and with high confidence.

Traditional FEA and CFD workflows require complex meshing, manual boundary setup, long solver runtimes, and specialist expertise. Physics-Intel replaces this fragmented process with a guided workflow that blends ML surrogate models, physics-informed constraints, and hybrid validation — delivering fast, interpretable results without sacrificing physical credibility.

Primary Objective

Accelerate engineering design decisions by transforming complex simulation workflows into guided, interpretable, and physically consistent insight — for structural, thermal, and fluid problems.

  • Faster structural and thermal optimisation across design variants
  • Early detection of failure zones, hotspots, and flow issues before physical prototyping
  • Rapid iteration of geometry, loads, and boundary conditions at simulation speed
  • More confident design decisions across cost, performance, and reliability
Vision
"To become the AI-native simulation layer powering industrial digital twins — starting with internal airflow and thermal systems, and expanding into broader structural and multiphysics domains."
Physics-Intel is not just a faster solver. It is a foundational intelligence layer that transforms how physical systems are understood, iterated, and optimised across industries.
Phase 1 · Now
Structural FEA · Thermal & CFD · Multiphysics simulation
Phase 2 · Next
Comparative analysis · Multi-variant optimisation workflows
Platform
Cloud-native · Scalable collaboration · API-first
End State
Live digital twin — persistent simulation layer for physical assets
Why Now
✓ AI-based surrogate modelling has matured enough for engineering-grade accuracy
✓ GPU infrastructure is widely accessible — inference is now viable in SaaS
✓ Digital twin adoption is accelerating across all target industries
✓ Legacy simulation stacks were not designed for foundation models or LLM-guided workflows

Get Started

Simulate Faster.
Design with Confidence.

Join the early access programme and get Physics-Intel running on your geometry — structural, thermal, or fluid — within 24 hours.

No spam · No commitment · We'll reach out within 24 hours

Structural FEA Thermal & CFD Multiphysics Automotive & EV Aerospace Industrial