Profile

I’m Yeseul Hwang,

an Go-to-Market startup strategist with hands-on experience as a founder, consultant, and product builder.

I specialize in helping early-stage AI, SaaS, and platform-based startups from business modeling to investor relations, and team building.

Since founding my first company in 2014, I’ve worked across industries, collaborated with public institutions, led product teams, and advised numerous ventures.
Today, through this blog(Eagler Lab), I share insights grounded in execution(not theory).


Career Timeline

  • 2024 – Present
    Partner Consultant, Knowhow Community
    Creator of EAGLER Lab (blog)
  • 2023 – Present
    External Consultant, Size Korea Project
    KATRI (Korea Apparel Testing & Research Institute)
  • 2019 – 2024
    Founder & CEO, AI Startup “Yesnow”
  • 2016 – 2019
    M.A. in Economics, Seoul National University
    Graduate Researcher, AIS Lab @SNU
  • 2014 – 2015
    COO, Manufacturing Startup
  • 2013 – 2014
    Exchange Program, Københavns Universitet (Denmark)
  • 2011 – 2016
    B.A. in Agricultural & Environmental Resource Development (AERD)
    Minor in Business, Seoul National University

Honor & Awards .

  • Jul 2023 – Seoul AI Hub Membership (1st Cohort)
  • Sep 2018 – 2nd Prize, Public Data & Big Data for Ag/Food Startup Contest
  • Jun 2018 – Best Application of Design Thinking Award
  • Dec 2017 – 3rd Prize, Agricultural Industry Management Innovation Conference
  • Feb 2016 – Seoul National University Graduation Thesis Excellence Award
  • Nov 2015 – 3rd Prize, Defense Technology Startup Competition
  • Oct 2015 – 3rd Prize, Superman Creation Audition
  • May 2013 – Best Paper Award, Korea Venture Startup Society Conference

Public Speeches & Lectures .

  • 2024 – Present – Ongoing consulting for early-stage startups
  • Apr 2023 – Guest Lecture, School of Computer Science, Ewha Womans University

Publications .

  • Currently in progress

Interests .

Entrepreneurship, Tech Strategy, Early-stage Startups,
Data-Driven Product Development, Business Model Validation