Quarrybank is the content engine built and run on a live publisher network first, giving editorial teams a system to find the right gaps, draft past a quality gate, and build topical authority that holds under algorithm pressure.
Most publisher teams already produce content at pace. The problem is producing the right content: the specific gaps where a site can actually rank, the topics where the search result is beatable, the angle that survives the next Google update because it is genuinely more useful than the alternatives. Without a structured discovery process, editorial calendars fill with ideas that feel good but compound nothing. Quarrybank was not designed in a vacuum. We built the engine to run our own publisher network, then productised it. The quality gate, the gap scoring, the AI Overview citation checks: all of them came from real editorial decisions on real sites. That is what makes this a tool for publishers rather than a repurposed keyword spreadsheet.
Radar scores every gap by difficulty, intent fit, and compounding potential so the editorial team picks from a shortlist, not a 10,000-row export.
Kenneth drafts and self-checks against a deterministic quality ruleset: answer-first structure, no padding, honest specifics. Editors refine, not rescue.
The engine tracks coverage gaps across your whole site, so each piece builds on the last rather than sitting in isolation. That is how moats form.
a month to run the data layer per site, versus a tool stack that climbs past £560
to quality-check a full article through the gate
Seam, Mill and Reserve. One site or a whole portfolio, the tier fits the operation.
Founding publishers get the full toolkit, quality gate, and a setup call at founding pricing for life. We are running the same system on our own sites right now. See also: Quarrybank for agencies and what a content moat actually is.
Request founding access