01 Think it through
AI Planning
Business diagnosis, requirements research, model selection and evaluation, workflow and agent design
Semiconductor · Electronics · Machining
What exactly is AI's place
in your factory?
We help manufacturers decide where AI belongs, get employees using it first, then turn high-value scenarios into small tools people can use directly.
Assess my scenario ↗ Our services → Take the 1-minute quiz →Diagnose first, then deliver. We start from your business problems, not from technology.
[ Plant / team photo: upload at Site settings → Hero image ]
People first — double efficiency with AI
Business first — make intelligence land
Three services — pick one, or follow the sequence
What we do
02 Build it
Tool Delivery
Role-based personal tools, plus mini apps for a single scenario
03 Use it
Training
For executives, employees and specific roles — everyone leaves with their role's toolkit
From business problems
Your questions,
answered one by one.
No jargon first. The problems you meet every day are the best starting point.
Tell us your problem ↗What does AI have to do with me?
Executive training: a workshop that shows what AI can do, what it cannot, and where the risks sit.
What can employees actually do with AI?
Training plus tools: document handling, report tidying, material retrieval — practiced on your real daily work.
Which step eats the most people, and what work is highly repetitive?
Business diagnosis: we map your processes together and turn the most labor-heavy, repetitive steps into a scenario list.
Which processes suit AI, and which don't?
Feasibility assessment: data availability, error tolerance and return — a clear answer on what fits and what doesn't.
What can we start using right away?
A scenario library: equipment Q&A, quality-exception assistant, document comparison — each can be piloted small first.
What AI foundation do we have, and what's next?
A readiness review plus roadmap: your systems, data and team capability, sequenced for the next 6-12 months.
Straight answers to what matters
Five things plant owners worry about
Wrong investmentDiagnosis and prioritization first; only 2-3 scenarios.
No resultsAgreed success criteria, a decision gate after validation, scale only on proof.
Data leaksPrivate/hybrid deployment; retrieval follows existing permissions; everything logged.
Staff won't use itRole-based training plus role toolkits they take back to work.
Which model fits?Public-cloud, open-source and domestic models evaluated on your real questions, with a written recommendation.
No industry jargon between us
We start from the artifacts you know.
SOPs, 8D reports, drawings, route cards, equipment manuals. We talk about what you do every day.
Equipment manuals / SOPs / specs
01
Equipment & Process Q&A
02
Quality Exception Assistant
03
Document Comparison Assistant
04
Policy & HR Q&A
Assessment and small-scale validation
Every step has a deliverable
Validate small, then decide on investment.
01
Diagnose
Map business pain points and data readiness into a scenario list.
02
Plan
Prioritize; set the roadmap and security approach.
03
Validate
Build usable pilots for 1-3 scenarios; let the floor try them first.
04
Deliver
Hand over on acceptance; train the user team.
After validation, a decision gate.
Against the agreed metrics and industry benchmarks: scale if it passes; adjust or stop if it doesn't — no blind extra investment.
[ Photo: upload in admin ]
About us
大飞，Founder
懂管理，懂行业，懂技术，懂流程，懂ai。 5年以上集团（企业）顶层设计经验，多次组织实施央国企五年战略规划； 10年以上数字化转型工作经验，为基础设施、新能源汽车、半导体、IT等领域的多家知名企业集团提供专业和创新的数字化转型咨询与实施服务； 10年以上半导体、IT行业的中高层管理实践经验； AI人专家，精通各类型llm大模型工具的私有化部署、训练（微调）、使用（知识库、agent）。