From Keyword Search to Goal-Driven Agents
Traditional B2B sourcing relies on directory lookups, phone calls, and trade shows. Agentic AI flips that model: buyers declare an outcome — category, unit cost, MOQ, certification — and an autonomous agent executes the multi-step search, validation, and outreach in parallel.
Why This Matters for Korean Brands
Korean beauty, food, and health brands face a two-sided discovery problem: channel partners abroad cannot assess product-market fit fast enough, and brand partners lack structured data to be discoverable. Agentic AI closes that gap.
The 72-Hour SLA in Practice
- 4 hours: inquiry received, PSS v4.0 first-pass scoring completed, match confirmed
- 48 hours: 3–5 candidate partners shortlisted based on PSS + channel fit
- 72 hours: final introduction and connection completed
What Buyers Should Ask
- Does the platform score products on real transaction signals, or only on metadata?
- Is the agent auditable? Can you see why a match was proposed?
- How is the feedback loop wired back into the scoring model?
Agentic sourcing is not "search + GPT." It is a measurable operating system for B2B matching.