Services
Laurelin Labs is an AI search consultancy. We make brands the source that Google’s AI answers, ChatGPT and Perplexity name, through ten services that run from a technical audit to team training, and two platforms we built: Newsroom for content teams and SPO for running a website’s weekly search work. Each service stands alone, so a client can start with one fixed piece of work. Agencies and consultants can also use us as their AI search partner, by referral or white label.
Agencies and consultants: take the two-minute tour
Services
AI Search Visibility work makes your brand and its leadership the cited, trusted source when buyers, investors and journalists ask an AI about your market. SEO competes on keywords; AEO competes on entities, and most organisations are currently invisible or ambiguous to the models.
A 387-point technical and AI-readiness audit. Every check is cross-referenced to a Google primary source and clustered into the Four Pillars of generative search, so you see not only what is wrong but why it matters and how to fix it. It surfaces the crawl, indexing, content, trust and entity issues that quietly suppress rankings and AI citations, with a fix list prioritised by competitive impact.
A Non-Commodity Content Audit scores every important page on your site for how far it sits from generic, commoditised content, the first-hand experience, real data and named entities that decide whether a page is worth citing. You get a page-by-page score with quoted evidence for every grade and a prioritised rewrite plan, so scarce content effort goes where it moves AI visibility.
A twelve-month AEO and AI-visibility roadmap built around priority topic clusters, keyword targets, content cadence, link priorities and AI-readiness actions, mapped to monthly milestones and your commercial goals. It is built for organisations that need one plan tying search and AI visibility to commercial targets, and it is strongest when grounded in a technical audit, an opportunity analysis and a competitor benchmark, so every milestone starts from where the site actually stands.
Two connected analyses: an opportunity gap that sizes the organic prize available to you in revenue terms, and a competitor benchmark across organic, paid and social that shows exactly where you are losing ground and what to fix first. Both are expressed in revenue terms so the size of the prize can be set against the cost of winning it.
A paid-search audit that surfaces wasted spend, negative-keyword gaps, quality-score and structural issues, paired with a strategy that sets budget allocation, campaign structure, audience targeting and a 90-day launch plan. The audit works from your own Google Ads account data rather than industry averages, so every recommendation carries the spend it recovers or the conversions it adds, and the strategy sets the measurement model before the first campaign changes.
A content strategy and production pipeline that turns raw material into SEO/AEO-optimised articles with structured data, author schema, internal links and People-Also-Ask coverage, designed so authority compounds to named authors, not just pages. Every piece must carry a unit of information gain, first-hand data, a named source or an original framework, before it ships, because commodity content is not cited by AI answer engines however well it is structured.
A four-layer operating system that captures every task (input), measures every metric (output) and joins them through an attribution model that survives a CFO conversation, closing the gap that gets agencies fired when the algorithm gives or takes. It is the reporting layer for every Laurelin engagement, so the question of whether the work moved the metric is answered with evidence rather than asserted.
A workflow-by-workflow map of where AI saves your team time, ranked by effort versus impact, with recommended tools, an implementation roadmap and a training plan so the capability sticks after the engagement ends. It covers marketing, content and analytics workflows first, because those are where language models return time fastest, and it documents prompts, guardrails and review steps so the team can run the workflows without us.
An end-to-end programme that runs technical audit, opportunity analysis, competitor benchmark, content strategy, backlink plan and a 12-month roadmap in sequence, then adds a new site build with optimised information architecture and full deployment. It is built for launches and relaunches, where starting from an AEO-ready information architecture costs less than retrofitting one, and every stage reuses the same 387-check register and Non-Commodity Score the standalone services run on.
Work with us
Seven slides: what has changed in search, where AI search fits in a B2B marketing system, the services and platforms behind the work, and the three partnership models. Use the arrows, the dots or your keyboard.
AI search partner for agencies, consultants and B2B teams
B2B buyers now research with AI first. Let’s make your clients the answer.
What has changed in search, the ten services and two platforms Laurelin Labs runs, and three ways agencies, consultants and in-house teams can work with us, starting with a free snapshot.
In the B2B categories we measured, Google shows its own AI answer above the results for most of the searches a buyer types. The answer names a handful of websites as its sources, and buyers read it before anything else, so the question for a brand is no longer only whether it ranks, but whether it is one of the names in that answer.
We pulled the live Google results for each search through the DataForSEO SERP API, on a desktop device: 355 UK workplace giving searches on 21 September 2026, and 11 US fleet telematics searches on 13 October 2026. For every results page we recorded whether an AI Overview appeared, which websites it named as sources, and where each of those websites ranked in the ordinary results below it.
| Category | Searches measured | Show a Google AI answer | Other finding |
|---|---|---|---|
| UK workplace giving (21 Sep 2026) | 355 | 92% | About 8 sources named per answer; 38% of sources on non-brand searches came from outside the organic top ten |
| US fleet telematics (13 Oct 2026) | 11 | 10 of 11 | 15% of top-ten results were YouTube, Facebook or Reddit pages |
The second finding in each row is the opening. More than a third of the sources Google named for UK workplace giving were not on page one, so a clear, well-evidenced answer from a smaller brand can earn a place before it earns a ranking. These are single-day desktop snapshots; mobile was not measured. Google’s own guidance points the same way: the work that earns a place in its AI answers is ordinary, well-made search work rather than a separate technique.
The best practices for SEO remain relevant for AI features in Google Search (such as AI Overviews and AI Mode).
| Model | How it works | Usually suits |
|---|---|---|
| Refer | You introduce the client, we deliver the AI search work, and you stay the main relationship. | Independent consultants in marketing, sales enablement or web |
| White label | We work behind you as your AI search team, under your brand and process. | Agencies that want to offer AI search without hiring for it |
| Direct and both ways | We work with your team directly, and refer our own clients who need what you do. | In-house teams, and partners whose services complement ours |
Fees are agreed per client: a referral arrangement or a wholesale rate for white label work. We would rather agree one client to try first than sign up to all three models at once.
With a free snapshot of one client: the questions that client’s buyers ask, which of them show an AI answer, which brands those answers name, and a ten-page audit of the site. We bring it to a 30-minute call so the first conversation is about the client’s numbers. The usual next step is a small fixed project, such as rebuilding the three to five pages closest to being quoted, then a light monthly scoreboard in Site Performance OS. Request a snapshot in the tour above, or email piers@laurelinlabs.com.
The field notes
Sent occasionally, never noise. The thinking behind the work, and the experiments before they ship.
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An AI search partner does the search work behind your client relationship: finding the questions buyers ask AI tools, checking whether answers name the client, fixing the website so it can be quoted, and reporting the results each month. You keep the client; the partner brings the specialist method and tooling.
Yes. White label work is one of the three partnership models. Laurelin Labs works behind you as your AI search team, under your name, with your client as the main relationship.
No fixed minimum. Every service can run on its own, so a client can start with a free snapshot or one fixed piece of work, such as rebuilding three to five pages, before committing to anything monthly.
The questions a client’s buyers ask, which of those show an AI answer, which brands the answers name, and a ten-page audit of the client’s site. It is free and carries no obligation.
