// Operator case study ยท greenfield build no. 3
Zero to first revenue in nine months.
The situation
Omnibound sells AI search marketing, helping brands win visibility inside AI answers. New category, no inherited GTM infrastructure, no playbook to copy, and scale-up expectations on pipeline.
The usual answer is to hire a marketer, two SDRs, and a RevOps contractor, then wait two quarters for the machine to assemble itself. That is roughly 400 thousand dollars a year in loaded headcount before the first meeting is booked. The mandate here was the opposite: one GTM engineer, one system, and revenue accountability from day one.
The build
Phase 01 · Strategy
Strategy compiles first
Before any tooling: TAM sized, ICP defined, personas mapped, and first, second and third party signal sources selected. Which job posting patterns, stack signatures, website visitors and LinkedIn behaviours actually indicate buying intent. The engine was designed on paper before a single API key existed.
Phase 02 · Engine
Full stack live in under three days
An end-to-end chain that had previously been a two week deploy was engineered, tested and sending in under three days. 150+ domains and 300+ mailboxes warmed and orchestrated, with deliverability engineered before volume rather than after it broke.
Phase 03 · Workflows
Unattended workflows layered on top
A seven stage LLM copy engine running with no human review, agentic research that took six hour batches down to under thirty minutes, 500+ personalised ABM landing pages tracking Share of Answer, RB2B visitor de-anonymisation, and the full event and webinar engine. Every one wired into CRM instrumentation.
Phase 04 · Revenue
The loop closes on revenue, not activity
Attribution ran through a self-built instrumentation layer, so every closed deal traced back to the signal that started it. Five customers closed, eight opportunities qualified, twenty eight deals in active follow up.
Why this is worth reading
The interesting part is not the tooling. It is that the system kept running without anyone babysitting it, and that every decision it made was traceable afterwards. That is the difference between a workflow and a system, and it is the only thing I am really selling.