What we do.
Three questions every B2B team has to answer in 2026. Can buyers find you in AI search? Do AI systems understand what you do? Are your marketing, sales, and CRM operating as one system? Our work is structured around those three questions.
If AI doesn't cite you, you're not in the category.
Traditional SEO still matters, but it's no longer enough. AI Overviews cut position-1 organic click-through by 58% in 2025. ChatGPT and Perplexity cite passages, not pages. Only 12% of the URLs cited by ChatGPT, Gemini, and Copilot overlap with Google's top 10. A site optimised only for Google is now a site optimised for a shrinking surface.
We do the two disciplines that solve this together. Buyers now ask questions in AI tools, but many company pages don't give those tools a clear, supported answer to use. We fix that with short answers, usually 40-60 words, backed by evidence and written around the questions buyers ask. Technical SEO at the infrastructure level, where crawl architecture, canonical strategy, AI crawler access, and structured data are what make everything above actually work. One depends on the other.
AEO for B2B →
Passage engineering, query fan-out, structured data, AI citation tracking. The discipline that gets you cited by ChatGPT, Perplexity, and Google AI Mode.
Technical SEO at scale →
Crawl architecture, canonical strategy, Core Web Vitals, AI crawler access, structured data estates. The infrastructure that makes AEO possible and ranking durable. We run this discipline across a 500,000-article B2B media archive.
Content grounded in client work. Hubs that compound. No regurgitated templates.
Most B2B content is interchangeable because most B2B content is generic. Ten agencies writing "the ultimate guide to B2B marketing" produce ten variations of the same article. None of them rank, none of them get cited, none of them change a buyer's mind. The only durable content moat in 2026 is proprietary data and decision history, combined with a hub-and-spoke architecture that survives at scale.
We do content strategy as a systems discipline rather than a calendar exercise. Topic clusters designed against real query fan-outs. Editorial grounded in evidence from audits, client work, and a decade of SEO lessons. Hub architecture built to last a decade, because B2B topics compound over years. Every piece traceable back to either a buyer-intent query, a client engagement, or a decision we've documented and can defend.
Marketing, sales, and CRM running as one system.
Most buying groups pick their preferred vendor before they ever talk to sales (94%, 6sense). Tracking tools see only a small part of that journey (around 3%, Chris Walker at Passetto). We build the CRM and RevOps layer that connects the signals you can capture to the pipeline they influence. A CRM optimised for the sales rep's pipeline view is a CRM missing most of what actually happens. The winning RevOps builds in 2026 are built around the buyer's rep-free journey, with declared-intent capture, self-reported attribution, and AI-augmented outbound stacked into one operating system.
We run this as two disciplines that reinforce each other. HubSpot and RevOps architecture, configured around declared-intent triggers and lifecycle automation that respects buyer behaviour. AI marketing operations, built on a semantic knowledge base (what we call the Open Brain) that gives every workflow persistent context across Apollo, HubSpot, Slack, and Claude. Most agencies do one or the other. We treat them as one stack.
RevOps and HubSpot →
Lifecycle automation, self-reported attribution, declared-intent triggers, dashboard architecture. The CRM build that turns dark-funnel buyer behaviour into something your team can act on.
Paid media →
LinkedIn-led paid, wired into your content estate and CRM. Built for qualified pipeline, future-buyer salience, and measurement against opportunities rather than MQL volume.
AI marketing operations →
Semantic knowledge base setup, MCP connector wiring, voice sample collection, scheduled workflows, prompt library. The infrastructure that makes every other workflow compound instead of starting from zero.
Three engagement shapes. Public pricing on all of them.
A 3-4 week diagnostic engagement in one service area. You leave with a prioritised decision, whether or not we build the fix.
A fixed-scope implementation project, 8-16 weeks, that takes one area from audit findings to working infrastructure.
Ongoing embedded work across one or more service areas. How most of our long-term relationships are structured.
Not sure which service area is the right starting point?
Tell us what you're trying to solve, and we'll tell you which service area to start with, which engagement model would work, and whether we're the right agency for it at all.
Book a call →