From GTM workflow audit to a working prototype on the client's real revenue systems in two weeks

Working with the client, we moved past an isolated AI demo and designed a buildable operating model that connects the GTM systems, business rules, approval gates, and learning loops, so they could scale real revenue execution without losing operational control. Built on the client's live data (HubSpot, Apollo, Clay, sequence history, and campaign performance), the system turns revenue inputs into business outcomes: enrichment, ICP scoring, and suppression checks route leads through review queues, while enriched context fuels company and contact briefs, campaign recommendations, and email sequences. Leads the agent is unsure about route to a review queue with their rationale, so an operator can approve, enrich, or reject in one place, and every decision improves future runs.