Most AI spend gets trapped in isolated productivity gains. I start with the workflow that can move the business, then deliver a live agent system running in your cloud within 8 weeks, with a dashboard showing the money it saved you.
I start by narrowing the field. Each candidate workflow is scored for business value, repeatability, data readiness, risk, and production complexity.
Not every workflow is worth automating. I find ones with high return and high feasibility that can deliver strong ROI.
I map how the workflow actually runs across your teams and systems. Then I redesign the process and build the AI agent system to handle it.
LLM choice comes after the workflow is clear. I'm provider-agnostic, choosing the LLM and deployment path that fits your privacy, latency, and cost needs.
I deploy the agent system on your cloud, with monitoring, human approvals, and documentation. Your team can trust and operate it from day one.
Your infrastructure, your data, your control. The entire system runs inside your environment.
AWS 
Azure 
Google Cloud After launch, I quantitatively track agent performance and improve it with structured evaluation loops.
I don't just hand you an agent and walk away. I stay until it pays off.
