We are

In the era of AI search, we design how brands are perceived by AI.

We use AEO (Answer Engine Optimization) to improve how your brand is cited in AI answers, and ABO (AI Brand Optimization) to help enhance your company's brand value.

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Mission

Our Mission at AI Archive

Our goal is to go beyond simply existing in AI search and recommendation environments — we aim to make brands accurately understood and preferentially mentioned. We transform answer engine optimization, the next step beyond search result optimization, into a practically implementable structure.

Enhance Brand Understanding

We organize brand structure so AI can more accurately assess the brand's role, expertise, and competitive advantage.

Strengthen Recommendability

We design citable assets to ensure stable inclusion in recommendation candidates that match query context.

Accumulate Execution Data

We accumulate repeatedly observed patterns from projects as datasets to accelerate decision-making.

Strengthen Trust Signals

We organize authority, expertise, consistency, and source structures so AI reads the brand as trustworthy.

Technology

Our Technology & Approach

Technology is not just a tool but part of the judgment system. We connect AI response collection, brand mention tracking, search result comparison, structured data design, entity consistency review, and AI reporting and monitoring in one flow.

Analytics layer

Response Observation & Comparative Analysis

We collect response documents by query and compare with competitors to see in what context brands are exposed.

Optimization layer

Content & Entity Alignment

We align page structure, brand introductions, citable information, and external trust assets to point in the same direction.

Reporting layer

AI Reporting & Monitoring

We organize platform-specific exposure changes, mention frequency, and positions in comparative queries into monthly reports and continuous monitoring systems.

Query Simulation

We separate brand name, category, comparative, and recommendation-type queries to observe response patterns.

Structured Information Design

We arrange organization, service, FAQ, and key personnel information to be easily understood by AI and search engines.

Iterative Verification Loop

Through ongoing monitoring, we confirm that exposure rates improve and brand positioning strengthens.

Advisors

Advisory Board

Our advisory professors and legal counsel support AI Archive's service direction and governance.

Advisory Professors

Professor Sung-Bae Cho, Yonsei University

Professor of Computer Science; Dean, Yonsei Graduate School of Artificial Intelligence; Vice President, Korean Institute of Information Scientists and Engineers Yonsei Fellow (2023), Order of Merit for National Service from the Korean Government (2022), Yonsei Underwood Distinguished Professor (2021), Gaheon Academic Award (2017), KIISE Academic Award (2005)

Professor Chang-Won Lee, Hanyang University

Professor, Hanyang Business School (OSM track) and Healthcare Management track President (19th term), Global Management Association

Professor Won-Sang Yoo, Korea University

Vice Dean, KUBS MBA and Executive MBA (EMBA) programs; Lead Professor, Marketing Vice President, Korea Society of Distribution Management; Director, Korean Academic Society of Business Administration Expert driving growth of the EMBA program

Legal Counsel

Attorney Young-Jun Kim

Present: Managing Partner, Samwoo Law Firm Former: Chief Prosecutor, Changwon District Prosecutors' Office Former: Director-General, Ministry of Justice Immigration & Foreigner Policy Bureau Former: Tax Legal Counsel, Seoul Regional Tax Office Amended Commercial Code: Corporate Auditor System (1984); Criminal Procedure Interpretation (1997) Award: Presidential Commendation (1996)

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