I build the systems that make GTM numbers trustworthy — then use them to make GTM strategy work.

Most GTM advice comes from people who've only sat on one side of the table — either inside an operating company, or outside as a consultant. I've done both, twice over.

At Strategy& (PwC), I lead GTM value-creation programs for private equity-backed SaaS companies — redesigning quote-to-cash motions, sales structures, and incentive models across 10+ engagements. Before that, at SBI Growth Advisory, I advised high-growth B2B SaaS companies on GTM strategy and commercial diligence for C-suite and sponsor audiences.

In between, I operated. At Voxel AI, I built the RevOps function from the ground up — architecting Salesforce, standing up the tech stack, and designing the data infrastructure that made forecasting and pipeline reporting actually reliable. I took quota attainment from ~30% to 105%.

That combination is the point. I've seen how GTM orgs get architected in ways that make board-level numbers impossible to trust without manual cleanup — and I know how to fix that at the data layer, not just the strategy layer. I'm also AI-native: I build agents and internal tooling (in Claude Code, VS Code) to speed up analysis and cut the resourcing needed to get there.

Based in New York.