STAR-T is an organization that helps decide if AI should be used
We don't implement AI for you.
We help decide if AI should be implemented.
Together, we determine if AI should be used
STAR-T distinguishes between problems where AI can be used and those where it cannot.
We work together to define the boundaries between what AI should do and what humans should do, handling only cases where responsibility and risks are clear.
We directly operate AI services that implement those decisions in code.
Mission
We decide together if AI should be used, and build structures where those decisions are implemented in code. We work together to define how far to automate, so people can work with less stress.
Vision
We aim to become the most trusted partner in determining AI usage, enabling all organizations to build structures together where people don't break down even when using AI.
Change through innovation
Purpose
STAR-T distinguishes between problems where AI can be used and those where it cannot. We work together to define the boundaries between what AI should do and what humans should do, handling only cases where responsibility and risks are clear.
STAR-T's Journey
We ran small-scale lectures on how to determine if AI should be used, and reviewed each participant's problems together. Based on this, we organized 300+ "AI usage decision" cases across 20+ domains into prototypes and business plans.
Building on this, we delivered 100+ lectures and consulting sessions for "AI adoption feasibility assessment" projects for startups and enterprises, with an average satisfaction of 4.7/5 and high practical value.
As with that satisfaction, we continuously gather feedback and develop our lecture/consulting offerings together. We will provide services built through this process.
View Key HistoryValidated in fields where judgment is needed
AI Usage Decision Cases
350times
Cases decided together through lectures and consulting
Average Satisfaction
4.7/5
Satisfaction with results decided together
Decision Criteria Organized Together
300+
Criteria for determining AI usage together
Fields Decided Together
20+
Determined AI usage across various fields together
STAR-T team members decide together if AI should be used
A team with experience structuring complex decisions and organizing responsibility and risks together
STAR-T Team
AI Usage Decision Experts
We bring proven expertise from 300+ "AI usage decision" experiences and 50+ lectures on "how to determine if AI should be used."
🏆 What We Do Together
📈 Results Decided Together
🌟 Career Highlights
300+ AI usage decision cases
Decided together with organizations from startups to enterprises
50+ decision method lectures
Lectures on 'how to determine if AI should be used' for government, universities, and enterprises
10B+ KRW investment support
Investment fundraising strategy based on results decided together
4.7/5 average satisfaction
High satisfaction with results decided together
🎯 Our Philosophy
"The core is not simply adopting AI, but deciding together if AI should be used. All lectures and consulting are built on real "AI usage decision" experience, with helping clients make their own decisions as our top priority."
🎓 Fields We Work In Together
AI Usage Decision
Organizing Responsibility and Risks
Implementing Decision Criteria in Code
Designing Structures for People to Work with Less Stress
Organizing Automation Scope and Criteria
Investment Support
🏆 Organizations We Decided With
Government
FSC, MOHW, KISED, etc.
Universities
Sogang, Sejong, Pusan, Kangwon, etc.
Enterprises
Kakao, Kia, Shinhan Financial, etc.
Startups
300+ startup consulting and mentoring
Core Values
Values STAR-T pursues
Clear Criteria
We work together to establish clear criteria for determining if AI should be used.
Decide Together
We decide together with clients whether AI should be used, and organize responsibility and risks together.
Clarify Responsibility
We clarify who is responsible when using AI, and design systems so people don't break down.
Work with Less Stress
We build structures together where people can work with less stress even when using AI.
STAR-T team members are more familiar with judgment than AI
A team with experience structuring complex decisions and organizing responsibility and risks together
Decision Criteria Implementation Team
We implement decision criteria organized together into code.
AI Usage Decision Team
We decide together whether AI should be used, and organize responsibility and risks together.
Decision Method Education Team
We learn together how to determine if AI should be used.
Is this a problem where AI should be used?
Let's decide together. After clearly organizing responsibility and risks, we build structures together where those decisions are implemented in code.
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