AI agents that move money.
I build AI systems that do real economic work: bill, pay, trade, rank.
Almost all AI ships with a human as the safety net. The model drafts, someone reads it before it goes out, and a mistake costs you an afternoon. I work on the other kind: systems that act, where the action is financial, irreversible, audited, and nobody reviews each one before it happens. That turns the engineering problem from accuracy into accountability. Audit trails, blast radius, escalation, and who answers when the agent is wrong. Billing is where I do this today, in regulated markets, which is the strictest version of the problem I've found.
Where I build
Platform briefed to Gartner and IDC · 99.7% config accuracy · 10× faster setup
Proof
Head of AI Programs, MaxBill. Production AI inside billing infrastructure, where an error is a compliance event rather than a bug report. Configures tariffs and complex B2B offers against regulator-auditable logic: 99.7% accuracy, 10× faster configuration. → MaxBill
Co-founder, LazySEM. A production SaaS for working SEOs: monitoring that catches a rogue noindex before traffic drops, briefs a writer can actually use, and cannibalization found before it costs you. It's the same failure class as billing, where systems break quietly and expensively unless someone instruments them. → LazySEM
AI Forex System. Running an AI-driven system with real capital. Results aren't published yet. When there's enough track record to be worth reading, it'll be here.