Search hasn't stopped mattering — it's split into three surfaces at once: the search results page, the AI answer, and the voice/snippet response. We build for all three, engineered the same way we engineer software.
Most agencies sell "SEO" as one service and quietly ignore the fact that a growing share of buying research now happens inside ChatGPT, Perplexity, Google's AI Overviews, and voice assistants — surfaces that don't work like classic search at all. We treat this as three distinct, related disciplines, each with its own mechanics:
Because we're the same senior engineers who build your site, we implement this at the code and infrastructure level — correct schema, real crawlability, genuine Core Web Vitals — rather than handing you a PDF audit someone else has to implement.
llms.txt manifests, citation-friendly content structure, consistent facts across the webWe start with a real audit — not a template checklist — of how your site currently performs across all three surfaces: Google Search Console data, structured data validation, and live testing against AI answer engines to see whether they can find, parse, and trust your content at all. Fixes are shipped in the same disciplined, peer-reviewed process as any other engineering work, then measured against the surface they were meant to improve.
1export const surfaces = {
2 seo: ["Google", "Bing"],
3 geo: ["ChatGPT", "Perplexity", "Claude", "AI Overviews"],
4 aeo: ["Featured Snippets", "Voice", "PAA"],
5 schema: ["Organization", "FAQPage", "Service"],
6};Specifics, not marketing language — this is what disciplined SEO, GEO, and AEO actually mean in our process.
Every JSON-LD block is validated against schema.org and Google's Rich Results Test on every deploy — not written once and left to silently break.
We check what a crawler and an AI retrieval system actually see — not just what renders in a browser — including JS-rendered content, robots directives, and canonical chains.
Your name, description, and facts stay identical across your site, schema, and third-party listings — AI systems weigh consistency heavily when deciding what to trust and cite.
Core Web Vitals are treated as a ranking input, not a side metric — the same performance budgets from our engineering work double as SEO infrastructure.
Key passages are written to directly answer a specific question in the first sentence — the structural pattern both featured snippets and AI citations favor.
We won't sell you a guaranteed position or citation — anyone who does is selling a lie. We report honestly on what's fixed, what's measurable, and what's still outside anyone's control.
Usually a GEO problem — missing or inconsistent entity data, no llms.txt, or content that isn't structured for extraction.
Common after a redesign or a plugin update — we audit, fix, and put validation into the deploy process so it doesn't silently break again.
We implement the fixes ourselves, in code, rather than handing you a list someone else has to execute.
Often fixable with clearer entity signals and answer-shaped content — not a full rebuild.
SEO optimizes for ranking in a list of blue links. GEO (Generative Engine Optimization) optimizes for being the source an AI system like ChatGPT, Perplexity, Claude, or Google's AI Overviews actually cites or paraphrases in a generated answer. It requires clean entity data, structured content, and machine-readable trust signals that classic SEO often ignores.
AEO (Answer Engine Optimization) targets the direct-answer surfaces — featured snippets, People Also Ask, voice assistants, and zero-click results — where a single well-structured passage gets pulled out and shown directly, without a click. It sits between classic SEO and GEO.
No — and any agency that promises a specific ranking or guaranteed AI citation is not being straight with you. What we can guarantee is the technical and structural foundation: correct implementation, valid structured data, clean crawlability, and content built the way search and AI systems actually parse it.
Both, if you want it. Many engagements start as a technical/structural audit and fix, then extend into ongoing content and schema work once the foundation is solid — fixing the foundation first is what makes the content work.