SearchD sets on a journey

SearchD is building answer engine optimization (AEO) for a specific, underserved gap: Korean brands that are well-established at home but effectively invisible in the AI-generated answers American buyers now rely on. A K-beauty serum, a baby carrier, a rice cooker – each may carry years of glowing reviews on Naver, ratings on Olive Young, and Korean press coverage, but none of that record lives on the English-language domains that ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews actually draw from. The result: when a US buyer asks “best sunscreen for oily skin” or “best Korean snail mucin serum,” the brand simply isn’t in the answer, but its competitors are.

Rather than competing for a spot on a page of ten blue links, SearchD works to get brands named directly inside the single AI-assembled answer a buyer receives. As the company frames it, ranking rewards depth, but citation rewards a passage an engine can lift whole – a fundamentally different kind of optimization than traditional SEO.

The process centers on a monthly “named rate” metric: a panel of about twenty representative buyer questions (“best Korean sunscreen for oily skin” and nineteen category variants) is run across the five major engines, and SearchD tracks how often the brand is actually named. Billing is tied to measurable movement in that number: if no cause is identified with a source page behind it, there’s no audit invoice, and if there’s no movement past the brand’s noise floor by day 60, the retainer stops.

The timeline SearchD publishes is specific: a free report lands within hours; a full audit identifying the cause behind every miss takes 3–5 days; the first correction goes live within a week; first movement (an answer that previously named a competitor starts naming the brand) appears in weeks 3–4; and the agreed target, set from the brand’s own measured baseline, is expected by weeks 6–8.

SearchD’s work spans four tracks:

– Source mapping and bridging – restating a brand’s existing authority, often stuck on .kr domains, onto domains that AI engines actually read, rather than simply translating it.

– US-first publishing – content written for an American reader from the first draft, not translated afterward, and syndicated across owned and third-party channels.

– Creator and reviewer outreach – working directly with the American reviewers, round-up writers, and subreddits (like r/SkincareAddiction) that AI engines quote and cite.

– Correcting factual errors – fixing cases where AI tools claim a brand isn’t sold in the US despite its presence at Target, Ulta, or Amazon; correcting confused Korean-to-US regulatory and labeling claims; resolving attribution problems where former distributors or same-name entities get credited instead of the actual brand; and surfacing Korean review and award evidence that US engines currently ignore in favor of competitor listicles.

SearchD is based in San Francisco and was co-founded by CEO Snow Lee, a serial entrepreneur. Lee personally handles SearchD’s free-report calls and runs the buyer-question panel.

Why now? SearchD points to a broader shift in how people search. According to OpenAI, roughly 900 million people were asking ChatGPT something every week as of February 2026, and Pew Research found that only about 8% of users click a link when an AI summary appears in search results, versus 15% when it doesn’t. The pitch, in short: search used to hand a buyer ten links to sort through; now it hands them one paragraph someone else wrote – and a brand is either named inside it, or not discussed at all.