I run organic and AI search for B2B SaaS companies. Most of my work is retained, six to twelve months or longer, as the person who owns the channel.
I have worked in SEO for 13 years. I have scaled sites past 1M monthly sessions, built programmatic content systems at 600,000 pages, and led organic growth at agencies and in-house.
My focus now is how SaaS products get discovered, evaluated and recommended inside ChatGPT, Claude, Perplexity and Google AI Overviews, and what has to change on your site, in your content, and across the sources those answers are built from before your brand shows up in them.
None of these came out of an audit. They came from running the channel week to week and staying accountable for the number.
Buyers now shortlist products inside AI assistants before they ever reach your site. I work out which questions matter commercially in your market, build the prompt set around them, and record where you appear, where competitors appear instead, and which sources the answers are drawn from.
That last part is the useful one. The citations tell you why a competitor is being recommended: a comparison page, a review site, a community thread, a doc you don't have. That becomes the roadmap for your own content, your technical setup and where the brand needs a stronger presence off-site. The tracking runs on a schedule after that, so you can see whether the changes worked. I built the tool myself, so the prompt set and the scoring fit your market rather than a vendor's template.
The job is producing the pages that enter buying conversations: category, use case, comparison, integration and problem-led content, plus the editorial work that earns citations elsewhere.
I build the topic map, write the briefs, run the AI drafting pipeline and do the editorial pass. Every client gets a written style rulebook, so the output reads the same whether the first draft came from me, your team or a model.
Technical SEO here means removing whatever is stopping your commercial pages from being found and understood, by crawlers and by the models reading them.
Site architecture, internal linking, rendering, indexing, schema and Core Web Vitals. I work directly in the CMS where I have access. Where the fix needs a developer, I write the ticket with the acceptance criteria already in it, then check it in production once it ships.
Keyword and topic mapping through DataForSEO, LLM visibility tracking, programmatic page builds, QA passes at volume. If a job would take 20 hours by hand, I write a script instead. That is what makes a large programme affordable to run, but the decisions still get made and reviewed by a person.
Share of search, LLM share of voice, assisted conversions, and a directional read on the channels last-click no longer covers.
I have spent years reporting SEO to finance teams, so the tracking I set up answers the questions they ask rather than the ones that flatter the channel. One report a month, written for your CEO to read.
I work inside your setup
Your Slack, your project management, your reporting. I join planning rather than running a separate consulting process alongside it, and I work directly with your writers, developers and product people.
I stay close to implementation
You won't get a strategy deck and a list of things for somebody else to figure out. I do the research, write the requirements, review the pages, chase the technical problems and see the work land.
I keep one prioritised roadmap
There is always more SEO work available than a company can ship. I keep a clear backlog, explain why things are ordered the way they are, and say no to work that looks good in a report but is unlikely to matter to the business.
I change direction when the evidence says so
The roadmap moves with what the data shows, not with what was agreed in month one.
Weeks 1 to 4
Technical and content audit. AI visibility baseline recorded. Competitor set and intent taxonomy agreed. Roadmap signed off.
Months 2 to 3
Technical fixes shipped. Content production running. Editorial standard written and in use. First movement in AI answers.
Months 4 to 12
Content velocity holds while the programme expands into new commercial topics and page types. Technical work continues as the site grows. AI-search visibility compounds as the cited sources change and new pages start being pulled into answers. Reporting shifts from traffic to pipeline influence, and the roadmap is re-cut each quarter against what that data shows.
This is the main way I work. I take on organic and AI search as part of your team: strategy, technical, content and reporting. Monthly retainer, usually six to twelve months.
In practice I am your SEO and GEO function. I sit in your Slack, join your planning, and carry the number.
I have enough experience in marketing and revenue operations to understand how search fits into the wider business, and I can work with your existing attribution, CRM and reporting setup rather than around it. But SEO and AI search remain the job.
For: B2B SaaS companies with no senior SEO in house.
The other two are usually how a retainer starts, rather than separate services.
A measured baseline of where you appear across ChatGPT, Claude, Perplexity and Google AI Overviews, against a competitor set and an intent taxonomy we agree first. You get the citation sources behind those answers, an explanation of why competitors are being recommended, and a roadmap for changing it. Runs on its own, or as the first six to eight weeks of a retainer.
For: SaaS teams who know AI search matters but cannot yet see where they appear, why competitors are winning, or what to change.
Topic architecture, AI drafting pipelines with a written editorial standard, programmatic page builds, and the QA pass that keeps them publishable. Scoped as a build, then handed over or kept under retainer.
For: companies that need more content without more headcount.
How identical tools and AI workflows have made SEO intellectually conformist, and why mental models, not tooling, are the real competitive differentiator.
There is less than a 1-in-100 chance that ChatGPT or Google’s AI will produce the same list of brand recommendations if you run the same query 100 times. This is the starting point for understanding why AI search attribution is a fundamentally different problem from traditional search tracking.
A guide on turning customer language from Google Reviews into structured messaging for website copy using a specific message-mining framework.
A few free tools I've built for common SEO jobs.
If you need someone to own organic and AI search at your B2B SaaS company, start a conversation or find me on LinkedIn.
I work with two or three retained clients at a time.