Simulation Software
Point modeling and analysis in specialized tools
YUANSUAN | ENGINEERING AI SYSTEM COMPANY
Yuansuan turns computation into intelligenceand intelligence into organizational capability
Our Engineering AI platform unifies engineering computation, production-scale runtime, and validation feedback so every computation becomes reusable, continuously improving organizational capability
Yuansuan System Path
PLATFORM × PROOF × SYSTEM
01Engineering Paradigm
Engineering is moving from tools to autonomy
Computation is becoming a continuous operating loop around engineering goals—not a one-time analysis
01
02
03
04North Star
Engineering Compute
Compute, data, and tasks run on one platform
Engineering AI
Models, knowledge, and tools work together on each task
Autonomous Engineering
Goals drive planning, execution, and validation
Core carrier
Specialized software
Compute platform
Engineering intelligence
Engineering system
Control model
Manual operation
Workflow orchestration
Human-AI collaboration
Goal-directed
Organizational form
Individual expertise
Team collaboration
Reusable methods
Compounding capability
01
Simulation Software
Point modeling and analysis in specialized tools
- Specialized software
- Manual operation
- Individual expertise
02
Engineering Compute
Compute, data, and tasks run on one platform
- Compute platform
- Workflow orchestration
- Team collaboration
03
Engineering AI
Models, knowledge, and tools work together on each task
- Engineering intelligence
- Human-AI collaboration
- Reusable methods
04
North Star
Autonomous Engineering
Goals drive planning, execution, and validation
- Engineering system
- Goal-directed
- Compounding capability
Engineering AI does not add intelligence to tools. It changes how engineering capability operates
02Organizational System
Complex engineering must run as a system
Objects, physics, workflows, and evidence are interdependent. Engineering capability needs one shared operating boundary
Objects Evolve
Structures, materials, boundaries, and operating conditions keep changing
Physics Interacts
Multiple physical domains, scales, and variables interact
Workflows Span Functions
Design, simulation, manufacturing, and operations move as one
Evidence Closes the Loop
Results stay reproducible, reviewable, and traceable
SHARED OPERATING BOUNDARY
Organizational Engineering System
Bring goals, context, capabilities, workflows, and evidence into one operating boundary
Goal alignment
Shared context
Capability orchestration
Process validation
Organizational governance
In complex engineering, competitive advantage comes from operating capability as a system
03The Yuansuan System
One Engineering AI system, from industry task to platform foundation
Tasks define outcomes. Solutions package capabilities for delivery. Products serve engineering roles. The platform runs it all
Industry Engineering Tasks
High-value problems embedded in critical industry workflows
Automotive & Transportation
Advanced Manufacturing
Energy & Power
Water & Emergency Management
Solution Systems
Reusable capabilities composed into deliverable, acceptance-ready task systems
Verify with Confidence
Design Before Freeze
Predict Before Failure
Decide with Simulation
Product System
Purpose-built workflows for professional operation, standardized access, and autonomous execution
GEWUExpert-Led Operation
LUBANStandardized Invocation
MOZIIntelligent Execution
Engineering AI Platform
One foundation for engineering computation, production runtime, and intelligence
Engineering Solving
Hybrid Engineering Solver
Scalable Runtime
Scalable Runtime Kernel
Engineering Intelligence
Large Engineering Model
Yuansuan turns industry problems into engineering systems that run, prove results, and improve through reuse
04Real-World Validation
Engineering AI must earn trust in real-world engineering
Granted invention patents, high-value engineering scenarios, geographic reach, and national-level industry recognition provide concrete proof of Yuansuan's engineering capabilities
129
Granted Invention Patents
Proprietary IP spanning engineering solvers, production runtime, and engineering intelligence
Engineering solverRuntime kernelLarge engineering modelEngineering applications
10+
High-Value Engineering Scenarios
Proven where constraints are tight, failure is costly, and accountability matters
Automotive mobilityAdvanced manufacturingEnergy and powerWater and emergency response
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Provincial-Level Coverage
Engineering capability deployed in real projects across regions and industries
Real engineering sitesCross-region deploymentMulti-industry operationContinuous capability reuse
National
National-Level ‘Little Giant’ Enterprise
National-level recognition of sustained technical investment and specialized capability
Deep specializationProprietary IPContinuous innovationLong-term engineering investment
CNNC
State Grid
SPIC
Zhejiang Energy
Dongfeng Motor
China United Engineering
iFLYTEK05Company Development
From engineering compute to Engineering AI infrastructure
Across technology, products, and market adoption, Yuansuan has advanced engineering capability from cloud runtime and proprietary solving to organization-scale operation
01
Cloud Engineering Compute
How can complex engineering workloads run reliably at scale?
Cloud engineering runtime
02
Autonomous Engineering Solving
Can engineering problems be solved autonomously and trusted?
Autonomous solving capability
03
Productized Engineering Capability
How can expert methods be reused across teams and tasks?
Standard product capabilities
04
Systemized Engineering AI
How can AI understand goals, orchestrate capabilities, and execute engineering work?
Engineering AI platform and products
05
Engineering AI Infrastructure
How do pilots scale across enterprises and industries?
Organizational systems and industry-scale deployment
Technology
HPC & Cloud Runtime
Proprietary CAE & Hybrid Solving
Engineering AI Platform
Goal-Directed Intelligent Execution
Product
Project Tools
Standard Methods
Engineering Utilities & Apps
GEWU / LUBAN / MOZI
Market
Strategic Partnerships with Industry Leaders
Mission-Critical Flagship Deployments
Cross-Industry Commercial Validation
Standard Products & Industry-Scale Replication
Make engineering capability runnable, solvable, reusable, intelligent, and scalable
06Open Engineering Ecosystem
The end state of Engineering AI is an open engineering ecosystem
Yuansuan is building open infrastructure where companies, experts, software partners, and institutions contribute, compose, and reuse engineering capability through shared standards
Open Technology
Connect specialized software, data, models, and compute environments
Open Capabilities
Make engineering methods discoverable, composable, and callable
Open Ecosystem
Enable partners to build industry applications together
Built by the Engineering Community
Enterprise customers
Universities and research labs
Software partners
Domain experts
Cloud and compute providers
Systems integrators
Foundation for Open Collaboration
Shared task protocol
Capability registry
Trusted runtime
IP and asset governance
Shared interfaces, trusted runtime, and clear ownership let more contributors build—and more teams reuse—engineering capability
07Compounding Assets
Turn every engineering outcome into a long-term enterprise asset
Each real task leaves behind reusable data, models, methods, and evidence—so organizational capability compounds over time
Data Assets
Objects, conditions, processes, and results become trusted datasets
Model Assets
Physics models, algorithms, and surrogates improve with every run
Method Assets
Workflows, rules, and expert know-how become callable capabilities
Evidence Assets
Benchmarks, review records, and acceptance criteria stay traceable
Capability Compounding
Individual expertise
Team playbooks
Organizational capability
Enterprise engineering system
Engineering AI compounds when every completed task makes the next one better
08Start a Pilot
PILOT VALIDATION
Start with one high-value engineering task
Prove the problem, integration, value, and delivery scope before scaling across the organization
01
Define the Problem
Set the problem scope, constraints, and acceptance criteria
Problem validated
02
Connect the System
Connect data, models, and engineering tools
System integrated
03
Prove the Value
Produce results and evidence in a real task
Value measured
04
Assess the Scale Path
Define how the capability will run and be reused
Method reusable
Enterprise Pilot Safeguards
Customer-owned assets
Tenant isolation and access controls
Auditable engineering data