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远算科技Yuansuan Technology

YUANSUAN | ENGINEERING AI SOLUTIONS

Put proven engineering methods to work across teams

Engineering capability that grows with demand

Compare options through simulation, check the results, then package the method as an App or workflow.

Explore solutionsDiscuss your business challenge

A NEW WAY OF WORKING

Build the engineering capacity your business needs

Reuse proven methods, scale computation and organize work intelligently so expertise can serve more people, projects and assets

Gaining experience

01
ProposePhysical testRevise
Explore optionsCompute & compareValidate

Learn gradually from limited alternatives, projects and tests

Explore more options computationally and validate new findings

Business value

Broader innovation and better development decisions

Supplying capability

02
ExpertOne task at a timeTasks waiting
Expert validationEngineering AppTeam use

Critical work depends on individual expert time

Teams call on proven methods through Apps and workflows

Business value

Wider access to expertise and more project capacity

Improving over time

03
Project AProject BProject C
Engineering dataEngineering AIEngineering use

Project experience and operating feedback remain scattered

Retain data, methods and evidence to update models and strategies

Business value

Company-specific capability and better products and operations

Experts lead exploration, judgment and validation. Engineering AI extends their reach.

SOLUTION AREAS

Design the future. Direct what comes next.

Find the right approach, from design optimization to operational decisions.

Intelligent design

  • Simulate before testing
  • Explore the design space
  • Compounding capability

Explore more design options and select within engineering constraints

Intelligent operations

  • Computation-driven intelligence
  • Connect implementation and operations
  • Improve continuously

Understand operating states, anticipate risks and compare strategies

BUILDING BUSINESS CAPABILITY

Turn completed work into reusable engineering capability

Turn validated methods into engineering Apps and pipelines, reuse them across projects and improve them through feedback.

01

Define the goal

Agree on the task, baseline and measures

  1. Business goal
  2. Current baseline
  3. Evaluation criteria
Use feedback in the next improvement cycle

Value for the current task

  • Better options and design rationale
  • Validation conclusions and review records
  • Risk assessments and operating strategies

Capability your business retains

Define business goals and the scope of asset use

Method assets

Engineering Apps and engineering workflows

Data assets

High-quality engineering datasets

AI assets

Specialist Engineering AI · Company-specific engineering models

Products that support capability building

Explore the shared Engineering AI platform
GEWU Engineering AI Workbench

Validate methods, publish Apps and train specialist AI

LUBAN Engineering Pipeline

Select Apps, compose workflows and run at scale

MOZI Engineering Agent

Understand goals, execute tasks and interpret results with feedback

RESULTS & EVIDENCE

Engineering evidence behind capability gains

Explore all case studies

Explore engineering results and their validation evidence, from wheel impact testing to cooling-source risk warnings.

Wheel 13° Impact Validation

Explore the full wheel case
Published case metricsPublished wheel-impact results · For this case’s conditions and assessment criteria
5/5Key checks passed
10.5%Minimum margin

Method validated

Impact response · Stress contour

Use loads, materials, and operating conditions to identify response regions that need further review

Capability ready for reuse

Engineering App results view · Illustration

Package validated methods and acceptance criteria in GEWU so teams can reuse them within their proven scope.

  • LUBAN · Orchestrate and execute
  • MOZI · Invoke intelligently
Engineering results
Compare digital and physical responses to locate differences and validate the method.
Reusable capability
Retain Apps, engineering workflows and validation data as a basis for Engineering AI training.
Delivery process and report structure4 types of published validation material
  • Response contours
  • Correlation curves
  • Acceptance report
  • Engineering App
  1. 01

    Set the baseline

    Confirm the wheel, materials, impact conditions, and correlation requirements

  2. 02

    Solve and review

    Analyze critical responses, correlate with tests, and conduct engineering review

  3. 03

    Capture outcomes

    Organize validation conclusions, model parameters, and reusable methods

Sample report layout

Sample report template showing results, criteria and review records.

START WITH YOUR APPLICATION

Start with your engineering task

Tell us about the engineering problem you are working on, and we will find a starting point together.

Initial outcome direction

Agree on the goals, first task and validation criteria

Capability to build

Plan reusable methods and Engineering AI

Discuss my engineering applicationExplore all case studies