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Engineering AI

From engineering intent to limitless exploration

Agentic engineering orchestrates the simulation process from intent to design, seamlessly managing complex workflows so teams can explore further, iterate faster, and build higher-performing products.

Trusted by 900,000+ engineers worldwide
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Core solution pillars

The intelligence layer between intent and validated design

Engineering AI transforms how products are designed & built.

Objective-driven engineering

Engineering has long been workflow-driven, with simulation runs defined step by step before insight is possible. Engineering AI changes the starting point. Engineers define performance targets, constraints, and trade-offs and the system orchestrates validation paths aligned to those objectives. Execution follows intent. Engineers focus on outcomes.

Agent-guided simulation

Engineering AI orchestrates simulation setup based on context and intent, selecting solver settings, mesh strategies, and boundary conditions automatically. Each validation cycle becomes repeatable, auditable, and scalable across teams. Experts can define templates, rules, constraints, and validation logic, creating reusable, governed workflows that encode your best practices.

Agentic reasoning, not task automation

Traditional automation executes predefined steps. Engineering AI agents reason about engineering intent. Agents coordinate end to end validation workflows. They interpret requirements, explore design alternatives, run multiphysics simulations, and assemble decision ready results within defined guardrails. Engineers remain in control. Agents handle orchestration.

Orchestrated, auditable execution

Engineering AI interfaces with users, agents, data, and compute. Every configuration choice, simulation step, and result is traceable and reproducible. Standards, templates, and compliance rules are embedded directly into execution, ensuring consistent validation across teams and programs. AI scales expertise. Governance preserves control.

Stop wasting engineering talent. When validation relies on simulation setup, expertise is consumed by process, not performance. Product innovation stalls.

See the SimScale Agent in action

How it works

From raw CAD file to instant design validation, in four steps

Engineering AI agents interpret your engineering intent, automate setup, and orchestrate execution from first conversation to final result.

01

Start a conversation at any time

The Engineering AI agent acts as an engineering collaborator and co-pilot within your workflow. The agent can interpret context, recommend strategies, and assist with simulation setup, execution, and evaluation, aligning each step to your product performance goals. Execution follows intent. Engineers focus on outcomes.

02

Let the agent work for you, as well as with you

Engineering AI applies reasoning, embedded templates, and data from over 1,000,000 public simulation projects to configure appropriate simulation strategies in minutes, not hours. By building structured validation paths with consistency and rigor, it accelerates workflows while preserving engineering control.

03

Build custom agents with organizational standards assured

Create custom agents to fine-tune behavior and oversight to your needs. Agents can be configured and published to embed company best practices, compliance requirements, and domain expertise across teams and programs, enabling your wider engineering workforce with guardrailed access to early simulation.

04

SimScale Workflows and APIs for multi-agent collaboration

SimScale's execution infrastructure is open by design — any solver, AI method, or external data source can be integrated natively into the platform, governed and versioned alongside SimScale's own capabilities. The result is coordinated, intelligent execution across the full engineering stack.

Built on industry-leading AI frameworks

Built on proven AI frameworks and accelerated computing, Physics AI models are trained on simulation data and grounded in physics — delivering reliable, engineering-grade predictions.

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Use cases

Where Engineering AI delivers measurable impact

Engineering AI reduces manual effort, accelerates iteration, and enables better decisions across the product development lifecycle.

RFQ responses

Use AI agents to orchestrate engineering work directly from an RFP/RFQ document. SimScale's Engineering AI interprets requirements, generates design concepts, runs physics validation, and assesses feasibility. Produce proposal-ready technical reports in hours, increasing your win rate and protecting your margins.

Code compliance checks

    Engineering AI interprets compliance requirements, configures the appropriate structural, thermal, or dynamic analyses, and maps results directly against code criteria. Generate audit-ready reports in hours — reducing risk, accelerating sign-off, and keeping projects on schedule.

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NPD acceleration

    Engineering AI autonomously runs parallel simulation workflows from early concept through to validated design — iterating through alternatives, surfacing performance insights at every stage, and documenting findings automatically. Teams reach confident design decisions faster and bring better products to market sooner.

    Learn more

Related resources

All Resources
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Explore our core technologies

Engineering AI works alongside cloud-native simulation and Physics AI — three technologies, one integrated platform.

Cloud-Native Simulation

SimScale puts powerful multiphysics simulation in every engineer's hands via an easy, instantly accessible web interface. Teams can explore, test, and share designs without friction.

Explore Cloud-native simulation

Physics AI

Instant prediction of physical behavior using AI models linked to high-fidelity simulation. Leverage past CAE data for instant parametric design optimization.

Discover Physics AI

Time is no longer the enemy. It’s your advantage.

Explore Engineering AI with SimScale.