AI Recipe: From AI Made for My Brother to a Brand Verification Engine
Session Overview
Unbound Lab researcher Lee Dong-hwi is drawing strong interest from consumer-goods companies after building an AI data-crawling model for entertainment management—originally created for celebrities such as his older brother, Cha Eun-woo (Lee Dong-min)—and demonstrating how it maps to product and brand verification in the real world.
He will unpack the key differences between AI-assisted and AI-native organizations—(1) impact on clearly defined problems, (2) output completeness that directly triggers action, and (3) the degree of domain-expert participation in designs such as RAG. Going beyond today’s many “foundation wrappers,” the talk walks through step-by-step development considerations for LLM/foundation wrapping that delivers measurable impact in industry.
Speakers
Mr. Cho leads investments at Unbound Lab, focusing on AI deep-tech and Commerce AI at pre-seed, as well as AIX investments in U.S. and Korean public companies. After roles at Accenture, IBM, Samsung Electronics, and Google, he now drives AI-transformation projects that boost efficiency and productivity, continuing successful AI bolt-on and roll-up initiatives in Korea. Together with an investment team of former AI developers and business consultants, Unbound Lab operates as a research-driven investor that delivers tangible operating results.
A media major with marketing experience at Cheil Worldwide and FengTai, Lee Dong-hwi conducts research and advisory work for Unbound Lab’s AIX bolt-on/roll-up investments. Known as the younger brother of actor Cha Eun-woo, he develops AI systems that combine multiple foundation models to solve niche, industry-specific problems—most recently extending an entertainment data-crawling model into a brand verification engine that consumer goods companies can deploy.