Recurring revenue architects for Enterprise GTM
60+
GTM Implementations
3 Layers
Intelligence, Orchestration and Activation
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We work with enterprise go-to-market teams that have outgrown their CRM setup. They've got the tools and the team, they just need the intelligence layer that ties it all together. Built on HubSpot and Clay, our systems connect what your team knows with what your data shows.
GTM Layer exists for enterprise go-to-market teams that have outgrown static CRM data and generic automation. We believe that RevOps has been tool-based and report-based for too long, and that the next generation of revenue operations is about intelligence, context, and systems that compound.
We layer intent signals, enrichment data, and CRM intelligence to surface the accounts worth pursuing, then build the systems that help your team act on them. From pipeline generation to closed-won reporting, every workflow is designed to compound over time, not just tick a box.
Every system and workflow is grounded in real revenue signals, not assumptions.
Senior RevOps operators only. No junior consultants, no account managers.
CRM, automation, outbound, reporting. Your entire revenue stack, not just one tool.
Systems designed for where you are heading, not just where you are today.
Fractional RevOps and GTM Engineering for teams that need more than CRM cleanup and reporting.
Even after the project is complete, we remain by your side, providing ongoing support and adjustments as needed.
Outbound failure is almost never a messaging problem. It is a systems problem. Deliverability, signal infrastructure, data quality, rep efficiency, and CRM integration all break before the email copy ever gets a chance to work.
Most outbound is list-based when it should be signal-driven. A full walkthrough of the six-stage Clay architecture that turns real buying signals into prioritised, enriched, personalised outbound at scale.
How GTM Layer runs its entire delivery operation on Claude, ClickUp, Fathom, and Miro. A transparent look at what works, what needed iteration, and why the compound effect of layered automations matters more than any single build.
