AI without measurable output is cost without return. I help organizations define what the work looks like, set the KPIs, and build the financial model around AI that actually performs.
Agents that own real responsibilities need real oversight. I design the governance structures, review loops, and escalation protocols that keep autonomous AI accountable inside enterprise workflows.
Digital workers need to be hired, onboarded, and managed. I build the operating model that treats AI agents like employees: with defined roles, clear success metrics, and a chain of command.
One agent is a pilot program. A workforce of agents is competitive leverage. I design multi-agent architectures that scale output without adding headcount across sales, recruiting, service, finance, and operations.
I help leaders turn AI into real digital labor that does actual work. My background spans recruiting, solution engineering, and enterprise AI strategy. I have built and operated businesses, sold and implemented enterprise software, and led teams deploying AI agents that own real responsibilities.
I approach AI the same way I approach hiring. You define the role. You design what success looks like. You onboard it into the day-to-day workflow. Then you coach it, review its performance, and improve it over time. When AI understands nuance and context, it stops being a demo and starts being a teammate.
At Asymbl, I work with companies to design bespoke digital workers across sales, recruiting, service, finance and operations. I spend most of my time with executives who are frustrated that their AI investments are not delivering results. The pattern is almost always the same: the problem is not the tool. The problem is the role design and the lack of ownership once the agent is live.