01
Technical search foundation
We inspect crawlability, rendering, index controls, canonical URLs, metadata, performance, sitemaps, content negotiation, and structured data.
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AI search optimization
Make your company easier for search and AI systems to understand.
AI search optimization starts with the same durable foundations as search optimization: crawlable pages, clear language, useful information, technical integrity, and evidence that supports what a company says. We audit those foundations, repair the gaps, and measure the public result across conventional search and AI-facing surfaces.
01 / Fit
When this work is useful
- Your site ranks for the brand but does not explain high-intent services on dedicated pages.
- Search engines can crawl the site, but its entities, proof, authorship, or internal relationships are unclear.
- Your team publishes useful material without a consistent information architecture or measurement loop.
- You need an evidence-based AEO plan without invented visibility scores or guaranteed rankings.
02 / System
What the system needs
02
Entity and evidence architecture
We make services, people, projects, sources, and their relationships explicit in visible copy and machine-readable markup.
03
High-intent content systems
We build useful service pages, case-study connections, FAQs, and internal paths around real customer questions rather than keyword repetition.
04
Search and answer-engine measurement
We establish verifiable checks for indexed pages, queries, referrals, citations, and site behavior while keeping external platform limits visible.
03 / Delivery
From workflow to production
The sequence is designed to expose uncertainty early and make the production operating model part of the build.
- 01
Establish the public baseline
Inspect the live site, search results, crawl paths, page templates, structured data, performance, and existing evidence before proposing changes.
- 02
Prioritize findability gaps
Separate technical blockers from content, entity, authority, and measurement gaps, then rank work by user value and verifiability.
- 03
Ship connected improvements
Repair templates and publish substantive pages with visible proof, descriptive links, consistent metadata, and matching structured data.
- 04
Verify the public surface
Recheck deployed HTML, mobile performance, index signals, Search Console data when available, and representative AI-search responses over time.
Relevant work
SearchEye
An agentic search intelligence platform designed around auditable recommendations, structured evidence, and human review.
Read the SearchEye case study04 / Boundaries
What we make explicit
- No agency can guarantee a ranking, citation, or answer-engine inclusion.
- Structured data must describe content that is visible on the page; it is not a substitute for useful content.
- AI crawler access, analytics referrals, and actual citations are separate signals and are reported separately.
- Independent authority is earned off-site and is not marked complete from on-site copy alone.
Frequently asked questions
Practical scope and measurement answers.
Is AI search optimization different from SEO?
The surfaces differ, but the foundations overlap. Search and AI systems both benefit from crawlable pages, clear information architecture, useful original content, accurate structured data, and credible evidence. AI-search work adds attention to how entities, sources, and concise answers can be understood and cited.
Can you guarantee that ChatGPT, Gemini, or Google AI Overviews will cite us?
No. Those systems choose and synthesize sources independently, and their behavior changes. We can improve the site's technical accessibility, clarity, evidence, and measurement, but we do not represent inclusion or ranking as guaranteed.
What does an AI search audit cover?
The audit can cover crawl and render behavior, index controls, page intent, internal links, entities, authorship, evidence, structured data, performance, machine-readable resources, and observed visibility. The final scope depends on the site and available owner-system access.
How is progress measured?
We separate implementation proof from outcomes. Deployment checks show that a fix is live; search and analytics systems can then show indexing, impressions, queries, referrals, or citations over an appropriate observation window.
Continue exploring
Related paths
Start with context
Bring us the workflow, constraint, or decision.
We will help determine whether the right next step is discovery, a focused pilot, or a production build.