AI search optimization agency · SEO + GEO + AEO
AI search optimization for Google AI Overviews, AI Mode, ChatGPT, Gemini, Perplexity, Claude and Copilot. See the audit, execution, measurement and limitations.
Written and reviewed by Aditya Aman, Founder and SEO Strategist
Last updated July 28, 2026 · Research reviewed against the live SERP
TheProjectSEO helps brands improve how accurately and often they are discovered across Google Search, Google AI Overviews and AI Mode, Bing, ChatGPT, Gemini, Perplexity, Claude, and Copilot. AI search optimization combines the parts of SEO that make pages accessible and competitive with prompt research, source analysis, entity clarity, explicit answer design, third-party corroboration, and repeatable visibility monitoring. The objective is commercially relevant inclusion and accurate representation—not a vanity citation count or a guaranteed recommendation.
Evidence, not theatre
The current public proof is limited to approved, point-in-time screenshots. The values below are shown with their source context and are not presented as guaranteed outcomes or universal benchmarks.
These are point-in-time measurements from screenshots supplied by the project owner, not promises or typical-client averages. Search and AI-response datasets use different collection methods and should not be added together.
Reserved for the approved Ahrefs AI responses and organic trend screenshots with the selected date range and metric labels visible.
AI discovery system
Expressway.PH AI visibility
Prompt set
Questions buyers actually ask
Answer review
Entities, claims and competitors
Citation check
Source, date and destination
Observe prompts and citations by platform. Never combine response counts with visits or rankings.
Reserved for a platform, exact prompt, answer, cited page, capture date, and factual-accuracy commentary.
AI discovery system
Dated citation walkthrough
Prompt set
Questions buyers actually ask
Answer review
Entities, claims and competitors
Citation check
Source, date and destination
Observe prompts and citations by platform. Never combine response counts with visits or rankings.
Scope and deliverables
The engagement starts with observable baselines and an evidence-backed roadmap. Execution combines website, content, entity, authority, and measurement work rather than offering a single “LLM optimization” switch.
01
A repeatable baseline across commercially relevant prompts, competitors, platforms, cited domains, and material brand facts.
02
A review of whether search and AI-related crawlers can access, render, interpret, and reach the pages that own important facts.
03
A page system that directly answers customer questions while preserving nuance, evidence, and a useful commercial journey.
04
Clear, consistent relationships among the organization, people, products, services, locations, evidence, and credible external profiles.
05
A source-led plan for earning relevant independent evidence rather than assuming the owned site can define its own reputation.
06
Controlled rechecks that distinguish platform volatility from meaningful change and connect AI visibility to search and commercial outcomes.
Find where your brand is absent, misrepresented, or supported by the wrong sources.
People use search engines and AI assistants together. A buyer may discover the category in Google, ask ChatGPT for options, verify a claim in Perplexity, visit a cited page, and return directly. A useful strategy covers the full journey instead of treating every platform as a separate trick.
01 · Learn
The user asks a broad question and expects a concise explanation, useful framework, or next step. The brand may earn visibility as a cited source without being recommended.
Example searches
Conversion event: qualified educational visit, deeper resource, newsletter, or relevant service path
02 · Explore
The user adds constraints and asks an AI system or search engine to compare methods, solution types, or trade-offs before selecting vendors.
Example searches
Conversion event: category, solution, methodology, or use-case exploration
03 · Shortlist
The prompt names a location, industry, budget, company type, requirement, or risk and asks which brands deserve consideration.
Example searches
Conversion event: brand search, service-page visit, comparison, enquiry, trial, or demo
04 · Validate
The buyer asks about reputation, proof, fit, pricing, implementation, alternatives, limitations, or a material claim before taking action.
Example searches
Conversion event: evidence review, sales conversation, product evaluation, or qualified opportunity
Most weak programs either rename ordinary content work as GEO or chase a black-box platform without fixing the sources those systems retrieve and trust.
Tracking hundreds of broad or synthetic questions can create an impressive dashboard while hiding whether the brand appears for real buyers, decision stages, locations, or products.
Our response
We build a versioned prompt taxonomy from customer language, search demand, sales questions, use cases, comparisons, and market constraints. Each cohort has an audience, intent, business route, and measurement purpose.
A model can name a brand negatively, cite it only as background, quote a third party, or recommend it without linking the company website. Those are not equivalent outcomes.
Our response
Reporting separates presence, prominence, sentiment or framing, factual accuracy, cited domain, cited page, recommendation context, and the commercial relevance of the prompt.
Important answers may be buried in vague prose, client-side interfaces, images, gated files, inconsistent product pages, unsupported schema, or content without a clear owner and date.
Our response
We improve crawl access, indexation, internal links, page ownership, explicit answer passages, fact tables, structured visible data, source attribution, and review governance.
AI systems may synthesize search results, publishers, reviews, directories, communities, partners, documentation, videos, and other sources when describing a category or brand.
Our response
We map sources used across important prompts, improve credible third-party corroboration, resolve entity inconsistencies, and create original assets worth citing. We do not manufacture reviews, citations, or consensus.
There is no universal “AI ranking factor.” Each experience has different retrieval, indexing, browsing, citation, freshness, personalization, and product behavior. The controllable work is improving eligible sources, brand facts, corroboration, and measurement.
Model outputs are probabilistic and can change with wording, account state, model version, location, time, and search activation. No agency can guarantee indexing, retrieval, a citation, a recommendation, or direct traffic. We record the test conditions and report observations rather than manufacture certainty.
Explore our AI search optimization servicePreserve the crawling, indexing, relevance, quality, and authority foundations used by search-backed experiences and conventional results.
Output: technical backlog, query and page map, search baseline, and implementation QA
Make important definitions, facts, criteria, processes, comparisons, limitations, and next steps easy to locate and quote without stripping context.
Output: answer inventory, page briefs, fact tables, and review requirements
Align what the site and credible external sources say about who the organization is, what it offers, where it operates, and why it is relevant.
Output: entity map, inconsistency log, profile plan, and structured-data changes
Identify which third-party sources shape important answers and improve the company’s legitimate presence through evidence, expertise, partnerships, and reputation.
Output: source graph, authority priorities, outreach angles, and correction opportunities
The first cycle establishes which prompts matter, what each platform currently returns, which sources shape the answer, and whether the website can support the required facts. Later cycles test prioritized changes.
Document audiences, products or services, markets, customer questions, material facts, existing entities, claim owners, conversion stages, competitors, and measurement access.
Delivered: commercial prompt inputs, entity inventory, claim owners, and outcome definitions
Run a versioned prompt set across agreed platforms, capture answers and citations, inspect search demand and landing pages, and map the sources repeatedly used.
Delivered: baseline, prompt taxonomy, source graph, competitor observations, and data limitations
Review crawl access, rendering, indexation, page ownership, answer clarity, claims, structured data, entities, internal links, and conversion routes.
Delivered: prioritized technical, content, entity, authority, and measurement backlog
Ship the highest-confidence technical changes, page improvements, new evidence-led assets, entity fixes, and structured data with subject-owner approval.
Delivered: released changes, reviewed content, QA evidence, and decision log
Strengthen credible third-party presence through original evidence, expert contributions, partners, profiles, relevant publications, and factual corrections.
Delivered: source assets, earned placements, corrected profiles, and corroboration progress
Re-run controlled prompts, compare cited sources and accuracy, inspect search and conversion cohorts, and separate persistent movement from platform noise.
Delivered: visibility report, experiment readout, confidence notes, and next roadmap
AI-search work still needs clear page ownership. A site that cannot explain its services, products, evidence, and entities to a human buyer will not become more trustworthy by adding FAQ schema.
| Page system | Search job | Example assets | Business signal |
|---|---|---|---|
| Category and definition | Help me understand the problem and available approaches | pillar pages, definitions, frameworks, glossaries, research, methodology | direct answer, scope, distinctions, evidence, expert ownership, and next step |
| Product, service, and use case | Can this brand solve my specific job? | service, product, workflow, role, industry, integration, and location pages | explicit offer, audience, process, boundaries, proof, and conversion route |
| Evaluation and comparison | How should I choose? | alternatives, versus pages, criteria, pricing, implementation, and fit | declared criteria, balanced differences, sources, limitations, and decision path |
| Evidence and trust | Can I verify the company and its claims? | case studies, authors, reviewers, sources, policies, methodology, and company | approved facts, periods, methods, named responsibility, and no invented proof |
| Third-party source assets | Where else can the brand be verified? | partner profiles, reviews, research citations, directories, publications, and video | independent relevance, consistent identity, substantive evidence, and current facts |
AI visibility is multi-dimensional. A commercially useful dashboard distinguishes whether the brand was present, how it was framed, which source was cited, whether the facts were correct, and what users did next.
AI assistants often do not pass a referrer, answers can vary between runs, and vendor tools use different prompt sets and scoring methods. We preserve prompts and test conditions, avoid adding incompatible platform counts, and do not claim direct causality without supporting data.
The share of a fixed, commercially relevant prompt set in which the brand or approved page appears, segmented by platform and intent.
Verified with: versioned prompt observations with platform, date, market, wording, and account state where known
Whether the brand domain or a relevant third-party source is cited, which page supports the answer, and where it appears.
Verified with: captured answer and citation URLs
Whether material company, product, service, location, price-boundary, and evidence statements are correct and contextually useful.
Verified with: approved fact register and human review
Impressions, clicks, page visibility, brand demand, and landing-page cohorts for related informational and commercial searches.
Verified with: Google Search Console, Bing Webmaster Tools, and approved rank cohorts
Qualified visits, enquiries, trials, demos, accepted leads, opportunities, pipeline, or revenue associated with relevant organic and known AI referrals.
Verified with: consent-aware analytics, self-reported attribution, and CRM where approved
The strongest programs treat AI-search visibility as an evidence, content, technical, entity, authority, and measurement problem—not as a shortcut around having a credible business.
FAQ
Continue planning
A focused explanation of GEO, retrieval, citations, sources, and execution.
Direct-answer architecture for search results and AI-generated responses.
Prompt cohorts, mentions, citations, sources, accuracy, and reporting.
Audit OpenAI search access, cited sources, brand representation, and referrals.
Test Claude discovery, selected sources, factual accuracy, and brand inclusion.
Clarify organizations, people, products, relationships, and corroborating evidence.
Strengthen the entity and source foundation behind Gemini brand discovery.
Apply Google’s published eligibility guidance to useful, extractable source pages.
Improve crawler eligibility, source usefulness, citations, and prompt-level monitoring.
Crawler access, rendering, indexation, internal links, performance, and release QA.
Share your products or services, audiences, priority markets, competitors, and existing AI-search reporting. We will map the highest-value prompt, source, technical, content, entity, and authority gaps.