AI Systems Architect · Agentic Orchestration
I build AI-native systems that run real operations — not copilots waiting for a prompt, but production-grade agents that vet, draft, schedule, respond, reconcile, and report around the clock, with humans stepping in only where judgment actually earns its keep. Typical result: 40–80% of the manual operational load, gone.
We're past the era of AI as a suggestion engine. The shift happening now is from assistive to agentic — systems that don't just recommend actions but take them. That schedule the meeting, send the follow-up, update the CRM, generate the report, and flag the exception.
Most businesses are still stuck chatting with AI. Summaries and first drafts are table stakes. The useful part is wiring models into the work itself: the handoffs, checks, follow-ups, decisions, and weird edge cases that should only hit a human when they actually matter.
This isn't about replacing people with chatbots. It's about building the operational layer AI-native from the start: agents doing the work, evals proving the work is right, observability tracing every prompt and tool call, and approval gates only where an action is irreversible. Five people running what used to take twenty — and knowing why it works, not hoping.
That's what I build.
Hundreds of brand channels
Operated concurrently by one orchestration layer — national brands, boutique operators, and review platforms.
9 in 10 actions, zero human touch
Approval gates reserved for irreversible, client-facing moves. Everything else runs autonomously, 24/7.
Hours → minutes
Response cycles across inboxes, reviews, and client requests — in the right voice every time.
8,000+ entities, tracked autonomously
A public-data platform ingesting from five upstream APIs on daily unattended schedules — no operator required.