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.