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Iurii Rogulia, senior full-stack software engineer. Professionally building software since 2001.

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TMI Iurii Rogulia
VAT ID: FI29845875
DUNS: 368664211
Lappeenranta, Finland 🇫🇮

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€800
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Iurii Audits: Technical SEO/GEO

€800

A developer's audit of why your site isn't showing up — in Google results and in AI answers. Fixed-price written report covering technical SEO, schema, indexing, AI-crawler access, and per-market keyword research.

Based in Finland (UTC+2) · VAT-registered FI29845875 · Respond within 24 hours

Recent client work

Wrongulator — The Calculator That Is Confidently IncorrectWrongulator — The Calculator That Is Confidently Incorrecteu-vat-rates-data — Free & Open-Source EU VAT Rates Dataseteu-vat-rates-data — Free & Open-Source EU VAT Rates Datasetvatnode — EU VAT Validation APIvatnode — EU VAT Validation APISee all projects →
Technical SEO/GEO Audit

Most SEO audits are run by marketers who can't read the code, or by tools that spit out a generic 300-page PDF. Neither tells you what's actually broken under the hood — and for technical sites, the technical layer is where the real losses are.

This is a developer's audit: I read your codebase, your rendered HTML, your sitemap, your structured data, and your Search Console — and I tell you exactly what's wrong, why it matters, and what to fix first. The deliverable is a written report. No call, no upsell, no monthly retainer.

Search is no longer only Google. A growing share of buyers now ask ChatGPT, Perplexity, or Google's AI Overviews instead of scrolling a results page — and those systems read your site through a different lens: what their crawlers are allowed to fetch, whether your pages answer a question in a form worth quoting, and whether the facts they need are machine-readable. That layer is what GEO (generative engine optimization) covers, and it's part of this audit, not a separate product.

I run technical SEO on my own site by default — schema.org, structured data, server-side analytics, llms.txt, IndexNow, automated broken-link scans. This audit applies that same checklist to your codebase, and tells you in writing what's missing.

What GEO is, in plain terms

GEO — generative engine optimization — is the work of being visible when someone asks ChatGPT, Perplexity, Claude, or Google's AI Overviews instead of typing a query and scrolling results. It is not a rebrand of SEO and it is not a growth-hack package. It is a specific technical layer, it is checkable, and most sites fail it by accident rather than by decision. Here is what it actually consists of:

  • Two different machines read you. One is a crawler (GPTBot, ClaudeBot, PerplexityBot, Google-Extended) collecting pages ahead of time. The other fetches pages live, while the user waits for an answer. They have different rules, and your site can pass one and fail the other.
  • An AI answer has no page two. A results page gives ten links and the user picks; an assistant names one or two sources and summarises them. Either your page is the thing being summarised, or your competitor's is. That is the whole shift in a sentence.
  • The most common finding is an accidental block. A default robots.txt, a WAF rule, or a bot-protection toggle nobody remembers enabling — and the assistants simply cannot read you. Fixing this is usually a two-line change with an outsized effect.
  • AI crawlers are not Googlebot. They generally do not execute JavaScript and wait for hydration. If your content only exists after the client-side render, they see an empty shell — the same failure mode SSR solved for search, showing up again.
  • Assistants quote statements, not vibes. A page that says "pricing on request" gives the model nothing to repeat. A page that states the price, the market, the delivery time and who it's for gives it something quotable — and that is what ends up in the answer.
  • Facts have to agree with each other. Your page, your structured data, and your llms.txt should say the same thing about price, location, and what you sell. When they contradict, the model drops you and cites a source it trusts more.
  • What GEO is not: there are no keywords for ChatGPT, no ranking positions to report, and nobody can promise you a spot in an answer. What can be measured is whether AI crawlers reach you, what they get when they do, and whether the assistants describe your business correctly. That's what the report covers — no invented metrics.

What's included

  • Per-market and per-language keyword research — actual search demand in the countries and languages your site targets, not a generic English list
  • Broken-link scan with Linkinator — every internal and external link checked; broken links cost crawl budget and tank user trust
  • Schema.org audit and recommendations — what structured data is missing, what's malformed, what should be added (Organization, Service, Article, BreadcrumbList, AggregateRating, FAQPage where relevant)
  • AI-crawler access review — whether GPTBot, ClaudeBot, PerplexityBot and Google-Extended can actually reach your content, and whether that matches what you want; blocked by accident is the most common finding
  • llms.txt review — the emerging standard for telling LLMs what your site is about, checked against what your site actually offers and charges
  • Answer-ready content check — whether your key pages state facts (prices, coverage, terms, who you serve) in a form an AI assistant can quote instead of paraphrasing a competitor
  • IndexNow setup check — instant indexing protocol used by Bing and Yandex; pings search engines the moment content changes instead of waiting for the next crawl
  • OG image recommendations — what's missing, what's wrong, how to make link previews work properly across LinkedIn, X, Slack, iMessage
  • Core technical SEO: crawlability, robots.txt, sitemap.xml, canonical tags, hreflang for multi-market sites, Core Web Vitals, indexability issues from Search Console
  • Written report (PDF or Notion) — prioritised findings, severity, and exactly what to change. No filler.

How I approach this

01

Access and scope

You share read-only access to Search Console, GA4 (if any), and the repo or staging environment. I confirm scope and target markets in writing.

02

Audit (3–5 working days)

I run the technical checks, do the per-market keyword research, validate schema, scan for broken links, review the rendered HTML, and check what AI crawlers see and are allowed to fetch. Evidence is documented as I go.

03

Written report

You receive a structured report: critical issues first, then quick wins, then strategic recommendations. Each finding includes the evidence, the impact, and the fix.

04

Implementation (optional)

The report is complete on its own — you can hand it to your own developers and we're done. If you'd rather I did the work, SEO & AI Search Optimization is a separate monthly service, and the €800 is credited against your first month if you sign within 2 weeks.

See SEO & AI Search Optimization

Terms & conditions

Fixed price €800, paid upfront. Delivered as a written report within 5 working days of access being granted.

No video call included. If you want a walk-through, book a Technical Consultation (€200) separately.

Scope is one site / one codebase. Multi-domain or multi-app audits are quoted separately.

Relevant projects

View all projects
Wrongulator — The Calculator That Is Confidently Incorrect
Wrongulator — The Calculator That Is Confidently Incorrect
May 31, 2026
Wrongulator — The Calculator That Is Confidently Incorrect

A joke calculator that returns a deterministically wrong answer with a straight-faced reason — built as a share machine.

eu-vat-rates-data — Free & Open-Source EU VAT Rates Dataset
eu-vat-rates-data — Free & Open-Source EU VAT Rates Dataset
February 25, 2026
eu-vat-rates-data — Free & Open-Source EU VAT Rates Dataset

Free, open-source EU VAT rates for all 27 member states + UK. Published as native packages for npm, PyPI, Packagist, Go, and RubyGems.

vatnode — EU VAT Validation API
vatnode — EU VAT Validation API
January 19, 2026
vatnode — EU VAT Validation API

Developer-first SaaS API for EU VAT validation via VIES with Redis caching, change monitoring, and webhook notifications.

Related articles

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IndexNow in Next.js: Instant Indexing After Every Deploy
April 14, 2026· 18 min
IndexNow in Next.js: Instant Indexing After Every Deploy

IndexNow implementation guide for Next.js: key generation, TypeScript client with retry logic, GitHub Actions workflow, and pitfalls that break submissions

Next.js Dynamic OG Images: Fix the Turbopack CPU Hang
February 28, 2026· 8 min
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Next.js dynamic OG images with Satori: why opengraph-image.tsx hangs Turbopack at 400% CPU, how API routes fix it, plus WOFF2 and Twitter card gotchas.

Technical SEO for Next.js: SSR, JSON-LD, and Sitemaps
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Technical SEO for Next.js: SSR, JSON-LD, and Sitemaps

Technical SEO built into Next.js: server-side rendering, dynamic meta tags, JSON-LD structured data, and automatic sitemap generation — no plugins, just code.

What Clients Say

View all reviews
“

I'd read about llms.txt and AI discoverability but had no idea whether any of it actually mattered for our SaaS docs site.

Dimitris Papadakis 🇬🇷

Founder

Topics

SEOllms.txtAIArchitecture
“

We publish 20-30 news articles per day and indexing latency was killing us — by the time Google crawled a story, the news cycle had moved on.

Andrei Popescu 🇷🇴

Engineering Manager

Topics

SEOIndexNowArchitecturePerformance
“

Our Next.js site was failing Core Web Vitals on mobile and we couldn't figure out why — Lighthouse scores looked fine locally.

Rita Almeida 🇵🇹

Co-founder

Topics

SEOPerformanceCore Web Vitals
Iurii RoguliaAvailable

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