AI AUTOMATIONVANCOUVER, CANADA

AI Automation Builder
with an Engineering Mindset

I design practical AI systems that organize information, reduce repetitive work, and improve operational decision-making.

PROCESS MAP / 01CONTROLLED SYSTEM
01Messy workflow
02Structure information
03Apply AI
04Validate output
05Reliable automation
AI-assistedHuman validated
ENGINEERING DISCIPLINEBUSINESS OPERATIONSAI AUTOMATION
01 / SELECTED WORK

Systems, not demos.

Practical automation concepts designed around real operational friction, structured inputs, and human review.

02 / THE APPROACH

From observation
to reliable output.

Automation works when it reflects the real process, makes assumptions visible, and keeps people in control.

01

Observe

Understand how the work is actually performed.

02

Structure

Convert scattered information into reliable data.

03

Automate

Connect scripts, APIs, AI models, and business tools.

04

Validate

Add checks, human review, failure handling, and traceability.

05

Improve

Measure results and refine the workflow.

INPUT CONTROLLED TRANSFORMATION OUTPUT
03 / BACKGROUND

Engineering is the throughline.

Across estimating, quantity surveying, engineering, and automation, the work is the same at its core: structure information, detect risk, and support better decisions.

01

University of British Columbia

Civil Engineering MEng

Engineering systems, analysis, and disciplined problem-solving.
02

Southeast Asia

Quantity Surveyor

Cost analysis, documentation, commercial awareness, and cross-functional coordination.
03

Canada

Construction Estimator

Scope interpretation, risk detection, assumptions, and decision support.
04

Current

AI Automation Projects

Applying the same structured thinking to information systems and operational workflows.
04 / CAPABILITIES

A practical, cross-disciplinary toolkit.

AI & AUTOMATIONBuilding with
  • LLM-assisted workflows
  • Prompt & context design
  • API integration
  • Workflow orchestration
  • Information extraction
  • Classification
  • Human-in-the-loop validation
TECHNICAL FOUNDATIONCurrently developing
  • Python
  • JavaScript & TypeScript
  • JSON
  • Git & GitHub
  • Data processing
  • Web application fundamentals
DOMAIN STRENGTHSApplied experience
  • Construction estimating
  • Cost analysis
  • Document-heavy workflows
  • Business process analysis
  • Quality assurance
  • Cross-functional communication
LET'S CONNECT

Interested in practical
AI automation?

Explore my professional background and connect with me on LinkedIn.

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