Enterprise platforms sell tooling. We sell methodology depth from the people who wrote the book.

Governance is the failure point most enterprise engagements hit at month six. The structural answer is a single methodology document that lives outside any one team — written, versioned, and binding across every property in the portfolio. We typically draft it as a 60-80 page playbook covering schema standards, internal-linking conventions, content review workflow, technical SEO acceptance criteria, and the escalation path when a property deviates. Each market or brand customises the local execution but cannot deviate from the core methodology without a documented exception. The deliverable is enforced through quarterly audits against the standard. Without that document, multi-site SEO becomes 14 different agencies running 14 different playbooks under one corporate budget — which is what most Fortune 1000 SEO programs actually look like internally before someone consolidates the methodology.

We embed in your engineering rituals rather than running parallel to them. That means we attend sprint planning, contribute SEO-tagged tickets directly to your backlog (Jira, Linear, ADO — whatever you run), and own the acceptance criteria for those tickets so engineering knows what 'done' looks like before they pick the work up. The technical SEO lead on our side acts as a product surrogate inside engineering ceremonies. We're explicit about what we own (the spec, the test, the acceptance) and what engineering owns (implementation, deployment, code quality). The pattern that fails is when an external SEO team writes recommendations into a PDF that engineering never opens — because engineering has no incentive to act on a PDF. The pattern that works is integration at the ticket level, where SEO work is just another type of ticket competing for capacity.

Yes, with caveats. Regulated industry content has to pass internal compliance, legal, and (in some categories) regulatory review before publication. We've built workflow for that: every piece of content has a defined review chain with named approvers, version-controlled drafts, and an audit trail of what was reviewed, by whom, and when. We write to the regulatory baseline of the category — proper disclaimers, source attribution, sourcing standards that match the industry's compliance posture. We're not a substitute for your in-house legal and compliance team; we're an external content operator that respects their authority and ships in their workflow rather than around it. If your industry requires specific certifications (HIPAA covered entity status, SOC 2, FINRA-registered review) we'll be explicit upfront about whether the engagement is in scope or out.

Three structural decisions drive multi-market success: site architecture (subdirectory, subdomain, or ccTLD per market), hreflang implementation at scale, and the localisation versus translation distinction. Architecture: most enterprise sites benefit from subdirectory structure (example.com/de/) for aggregating domain authority, but legal, regulatory, or hosting constraints sometimes force ccTLD. Hreflang: the implementation that breaks at scale is the one done in HTML head tags — at 100K+ URLs, hreflang has to live in the XML sitemap with automated validation against canonical conflicts. Localisation: machine translation produces ranking-grade content in fewer than half the language pairs people assume; the others need native-speaker editorial review or the content reads as inauthentic and Google deranks it. We map all three decisions before any work begins and document the rationale so future market expansions don't redebate them.

When the work you need is methodology depth and senior judgement, not platform tooling and headcount. Large enterprise SEO agencies (Conductor, BrightEdge, Searchmetrics-tier) charge for two things: proprietary platforms that aggregate competitor data, technical audits, and reporting; and dedicated headcount to operate those platforms across your portfolio. That's the right purchase when the bottleneck is platform-tooling and process maturity. A boutique enterprise operator like us is the right purchase when the bottleneck is methodology — when your in-house team has tooling and headcount but lacks the senior practitioner who can make architectural calls, design original-data research, or own the AI search transition end-to-end. Both models are legitimate. Pick by what your bottleneck actually is. If you don't know which one, that's a useful answer too — usually means the in-house team needs an outside diagnostic before any agency engagement.

Original-data research is the highest-leverage SEO asset an enterprise can commission and the one most enterprise teams underinvest in. The pattern: pick a question your industry is asking but nobody has answered with primary data, build a dataset large enough to publish defensible findings, and ship the research as a flagship asset that earns links, citations, and AI engine references for years. Our V2026 Ranking Study is the example — we built it as the backbone of our own outreach and it now anchors press relationships across the industry. For an enterprise client, the project usually runs three to four months: hypothesis design, dataset construction, analysis, methodology write-up, design and visualisation, embargoed pre-launch outreach to journalists, public launch, and ongoing citation monitoring. Budget is usually $100K-$300K all-in. The output earns ROI for years because original data ages well, gets cited compoundingly, and becomes the asset competitors have to argue against rather than ignore.

Both, depending on what the engagement needs. We're tooling-agnostic — if the client already pays for Conductor, BrightEdge, or Searchmetrics, we operate inside that platform rather than adding parallel cost. Where we add proprietary tooling is in disciplines those platforms don't cover well: AI engine visibility (we built Mention Layer for this — most enterprise platforms still don't track ChatGPT, Perplexity, Gemini, Google AI Overview properly), digital-PR citation building (PressForge), and original-data research workflow. We're explicit about which tools are ours, which are licensed third-party, and which the client already owns. We don't markup tooling costs and we don't bundle tools we don't actually use into the engagement to inflate the deliverable list.

Four common shapes. Strategic advisory ($25K-$50K/month) — quarterly strategy work, governance frameworks, methodology design, with execution handed back to the in-house team. Embedded execution ($50K-$100K/month) — we're part of the workflow, embedded in engineering sprints and content production, with named operators on our side dedicated to the account. Specialty discipline ownership (variable) — narrower scope, deeper expertise — example: we own AI search/GEO entirely while in-house owns content. Original-data research project ($100K-$300K project basis) — bespoke V2026-style study for the client's industry, with defined deliverables and a fixed timeline. Most enterprise engagements start in one shape and migrate over time as scope becomes clearer. We write monthly retainers as month-to-month with 60-day exit provisions, even at enterprise scale, because we'd rather earn the renewal than litigate the lock-in.