Enterprise SEO

What this is

This is not a generic SEO retainer. It’s enterprise and B2B technical SEO done by the team that builds your systems, so search is wired into your product and your funnel instead of running as a separate checklist someone reports on each month. The foundation underneath is the boring part done right: a site that search engines can crawl, understand, and rank, built that way from the first commit. It’s also what makes you eligible to be cited by AI, because AI search retrieves from the same indexes you’re trying to rank in. If you don’t rank, you don’t get pulled into an answer.

Why the AI shift makes this matter more, not less

There’s a common assumption that AI search makes classic SEO obsolete. The plumbing says otherwise. The retrieval crawlers behind LLM answers mostly fetch your raw HTML and don’t run JavaScript — an analysis of more than 500 million GPTBot requests found AI crawlers effectively don’t execute client-side JS. So a single-page app that paints its content after hydration looks empty to them. That’s a build decision, not a content one: render the page server-side and the content is there in the first response.

The other half is what actually moves AI citations. The original GEO study (KDD ‘24) tested this directly and found that adding cited sources, statistics, and quotations to a page raised its visibility in generative answers by up to ~40%, with citing sources the single strongest lever. That maps cleanly onto what good editorial SEO already does. The shortcuts don’t hold up: a 300k-domain study found llms.txt had no measurable effect on AI citations, and Google has folded “manipulating generative AI answers” into its spam policies. The durable play is the same as it ever was: a site that’s crawlable, well-structured, and worth citing.

How we build it

We render server-side so the content exists in the HTML before any JS runs — on Astro for content sites, or Next.js App Router on OpenNext for Cloudflare when the app needs more. Either way the crawler, human or machine, gets a complete page on first request.

On top of that:

• Structured data. JSON-LD per Google’s structured-data docs, typed against schema.org, so an Organization, Article, Product, or FAQ is unambiguous to a parser instead of inferred from markup.
• Core Web Vitals as a budget, not an afterthought. We hold the page to the web.dev Core Web Vitals thresholds — LCP, INP, CLS — and treat a regression as a build failure, because slow pages get crawled less and rank worse.
• Architecture and internal linking mapped to the queries that matter, so crawl depth and link equity land on the pages you want found.
• Measurement wired through GA4 so referrals from AI assistants and organic search are visible, not guessed at.

Where this is heading

Buyer research is moving toward AI intermediaries — Gartner expects AI agents to influence 90% of B2B purchase journeys by 2028. Whether a person or an agent is doing the searching, the requirement is the same: a fast, crawlable, well-structured site that a retrieval system can read and trust. We build that foundation once, then maintain it as the indexes and crawlers change.