AI Search Trust Engine

Become the Trusted Answer AI Recommends

UnderAI helps global brands that are missing from AI answers—or cited through scattered third-party sources—build public trust signals, answer-ready content architecture, and citation sources so AI systems can understand their value, recognize their authority, and cite their official sources.

Prompt strategy High-quality article strategy High-citation source strategy Website GEO optimization
Brand Definition
GEO helps brands establish a clear and trusted presence in AI-generated answers.
Service Scope
Includes AI citation and sentiment analysis, prompt behavior analysis, website content optimization, media-source planning, reputation maintenance, and reporting.
Best For
For brands asking whether AI mentions them, what evidence AI trusts, and whether their official sources can be cited.
Service Model
Global GEO and SEO AIO service with prompt-level and model-performance-based execution.

Why now

AI is redistributing exposure, trust, and opportunity

When AI recommends a brand, it is not merely showing a result. It is reducing decision risk for the user and lending trust to the brand.

01

AI screens choices

Users now ask AI to shortlist vendors, products, tools, and local services before they ever visit a website.

02

AI becomes a trust proxy

A recommendation from AI increasingly feels like a third-party endorsement, especially in high-consideration categories.

03

The window is open

AI recommendation patterns are still evolving. Brands that establish their presence early can build authority before AI recommendations become dominated by a small number of sources.

Trust diagnosis

Find Out Why Your Brand Is Missing from AI Answers

We diagnose not only whether you are mentioned, but whether AI has enough stable evidence to use your brand as a trusted answer source.

Answer eligibility

Where the brand drops out of the AI answer path

GEO
High-intent prompt"What is the best AI search optimization service for a B2B SaaS brand?"
Likely drop-off pointIdentify the High-Value AI Queries Your Brand Should Compete for First

We separate broad awareness prompts from purchase, comparison, risk, and support prompts so the diagnosis starts from real decision demand instead of a flat keyword list.

Signals we verify
Decision-stage prompt clustersCommercial value scoringCompetitor answer patterns
Repair priorityPrioritize high-intent prompts where AI already has demand but lacks a trusted brand answer.
If prompt demand is unclear, later content and source work will optimize for questions users never actually ask.

Echo Core Theory

Dual Trust Engines

AI recommendations are driven by two trust engines: one identifies who you are, and the other determines whether your official sources can be safely cited. Brands that build both engines become more stable answer sources in AI systems.

EchoLu dual trust engines infographic

Project SOP

Six delivery stages, from diagnosis to monitoring

This is the operational delivery model that turns GEO strategy into prompt assets, content/source execution, trust maintenance, and repeatable reporting.

01

Analysis and evaluation

  • Brand AI citation analysis
  • AI sentiment analysis
  • Category and competitor assessment
  • KPI planning and baseline setup
02

Prompt library setup

  • Prompt user-habit analysis
  • Decision-stage prompt clusters
  • Commercial value and priority scoring
  • Baseline prompt set for retesting
03

Website and content assets

  • Website GEO audit and optimization
  • Content matrix setup
  • Content direction design
  • Prompt debugging and content creation
04

High-citation sources and media matrix

  • Existing content analysis by prompt
  • Target-model source preference analysis
  • Media planning and strategy
  • High-authority distribution
05

Reputation and trust maintenance

  • Real-time brand monitoring
  • Deep reputation data analysis
  • Trust repair strategy
  • Brand credibility improvement
06

Monitoring, retesting, and reporting

  • Full-network target monitoring
  • Monthly data reports
  • Effect review and retesting
  • Next-stage strategy recommendations

Why UnderAI

From being mentioned to being trusted

Most GEO services stop at visibility. UnderAI focuses on trust, citation eligibility, and long-term answer-source status.

CapabilityUnderAITraditional GEO
Strategic goal
Trusted entityBuild the brand into a credible entity inside AI knowledge systems.
Mention trackingMeasure whether a model mentioned the brand.
Prompt research
Decision prompt systemMap high-intent prompts, blue-ocean opportunities, and buyer scenarios.
Keyword expansionConvert SEO keywords into more keywords.
Content strategy
Citable knowledge assetsWrite pages as evidence-backed answer assets with FAQ, summary, and source structure.
Generic AI contentPublish broad SEO-style or AI-generated content.
Authority building
Citation engineeringAlign official pages, high-authority media, vertical sources, and model preferences.
PR distributionPublish articles without connecting them to AI citation behavior.

Cross-industry GEO experience

GEO has already been applied across multiple industries

UnderAI has accumulated hands-on GEO experience across global SaaS, ecommerce, travel, EV, and technical product scenarios. We use these industry cases to identify recurring AI trust gaps and turn them into practical optimization paths.

Sample case / illustrative benchmark. Metrics are directional examples; definitions, period, and sample scope should be confirmed before publication.

Feature visibility in AI shortlists

Complex features, comparisons, and review pages cause AI to cite third-party lists instead of your product pages.

35%Before
78%After
123%

Why AI filters you out

AI cannot confidently map your product entity, feature set, security claims, and pricing facts across owned and third-party sources.

UnderAI fix path

Clarify product entities, implement SoftwareApplication schema, map comparison prompts, and identify the competitor sources AI is already using.

Answer eligibility lift
Feature recognition78%
Schema readiness82%
Competitor gap coverage74%

Talk to UnderAI

Find out why AI is not recommending you yet

See the prompts you are losing Identify the buyer questions where competitors appear, but your brand is absent, vague, or unsupported.
Find the trust signals AI is missing Spot source conflicts, weak official pages, missing schema, and evidence gaps that block citations.
Know what to fix first Get a clear repair path your content, PR, brand, and website teams can act on.
Talk to UnderAI Leave your email and our GEO team will follow up

A GEO consultant will contact you by email to understand your goals and suggest the right next step.

FAQ

Common questions

Answers to the questions teams ask before starting GEO: why AI does not mention your brand, which trust signals need repair, how results can be retested, and what your team should prepare first.

SEO primarily improves rankings, clicks, and organic traffic in search results. GEO focuses on whether AI systems such as ChatGPT, Perplexity, and Google AI Overviews can understand your brand, evaluate its official sources, and include it appropriately in relevant answers. UnderAI builds on established SEO foundations while extending the strategy to entity authority, answer structure, third-party evidence, and repeatable prompt testing.

More customers ask AI which company fits their need, whether a brand is credible, or what alternatives they should consider. If AI cannot recognize your brand, or only cites competitors and scattered information, you lose a recommendation moment before the customer reaches your website.

UnderAI is for global brands and marketing teams evaluating GEO, especially teams whose brands are missing from AI answers, described vaguely, cited through competitors or scattered third-party sources, or not yet supported by official sources that AI systems can understand, evaluate, and cite.

UnderAI helps organize real public evidence that AI systems can verify and cite, including official pages, FAQ and answer blocks, structured brand facts, media and citation-source planning, high-citation source strategy, and—when available—customer cases, reviews, certifications, partner evidence, or other third-party proof. The goal is to make real evidence easier for AI systems to find, understand, and verify, not to invent claims.

We build prompt tests around your brand, category, use cases, competitors, and high-intent questions. Then we check whether AI mentions you, how it describes you, which sources it cites, and what trust signals are missing compared with competitors.