Build Intelligence.
Move the World.

From systems and data to AI — we build digital products that actually work.

Windmill Technology

We bring software engineering, data engineering and AI together — from system architecture and full-stack development to LLM applications — turning complex requirements into products that ship, scale and keep iterating.

Global markets

Four markets, one delivery standard.

Clients across the US, Taiwan, Hong Kong and the UK. Transparent collaboration, a clear cadence and traceable development keep cross-region projects moving steadily.

US
United States
TW
Taiwan
HK
Hong Kong
UK
United Kingdom

Capabilities

Systems, data, AI — integrated by one team.

Seven core capabilities spanning product architecture, development, data engineering and AI — fewer vendors to coordinate, faster to a verifiable product.

Selected work

We don't just build products. We run them.

資料工程AI 分析Web 平台

PickNewCar

Specs, prices and needs in one place — car decisions with grounds.

Read case study
大數據即時資料視覺化

Stock Center

Market data brought together, so trends are easier to read.

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LLM運動數據多模型協作

3LLM AI Score Prediction

Multiple LLMs predicting side by side, cross-checked on every match.

Read case study

AI Lab

Don't just see results. Run it yourself.

Pick a sample dataset or upload your CSV, configure a model and watch training happen live — classification, regression, clustering and text analysis, all computed in your browser. Your data never leaves your device.

training · demo-042
Demo Mode · trains in your browser

loss

0.118

accuracy

0.96

epoch

40/40

loss accuracy
  • [queue] job #demo-042 accepted · priority normal
  • [data] 150 rows · 4 features · split 80/20
  • [train] epoch 12/40 · loss 0.412 · acc 0.87
  • [train] epoch 24/40 · loss 0.201 · acc 0.93
  • [train] epoch 40/40 · loss 0.118 · acc 0.96
  • [done] report ready · confusion matrix · feature importance

How we work

Every Sprint ships reviewable progress.

  1. Goals & Backlog

    Align on business goals and use cases; shape requirements into an actionable, prioritized backlog.

  2. Sprint planning

    One cycle every 1–2 weeks — scope, acceptance criteria and risks agreed upfront.

  3. Build & daily sync

    Short iterations with AI agents accelerating research, development and testing — problems surface before they cost time.

  4. Review & retro

    A demo at every Sprint's end, and a retrospective to make the next one better — the loop keeps running after launch.

Culture

Four Keeps. One rhythm.

  • Keep Trying
  • Keep Challenging
  • Keep Changing
  • Keep Improving

Parallel collaboration puts decisions next to the problem; AI agents free the team for higher-value judgment; internal startups turn ideas into products.

Meet our culture

Say the problem clearly, and the product starts moving.

Tell us your goals, current state and constraints — together we'll scope what's worth building first.