Your operation runs on the same agent stack I run mine on — in 16 weeks.
Discovery, build, and a ninety-day operator retainer bundled into a single SKU. The agent system I built for my own operations — CRM, prospecting, scheduling, analytics, ops — rebuilt for yours. Fixed scope, fixed timeline, fixed outcome.
Book a 30-Minute CallThe system, not a slide about the system
Most AI engagements end with a deployed system and a hopeful handoff. The Productized AI Stack ends with a deployed system that’s been running in your operation for ninety days — with me inside it, evolving it, watching adoption land, fixing the things nobody could have predicted at the scoping stage. The retainer isn’t a follow-on. It’s how I know the build worked.
The shape of the stack is based on what I run on my own operation: a multi-agent system that handles CRM, prospecting, scheduling, analytics, and the operational glue between them. It’s the same architecture, sized and adapted to your business. Not a demo. Not a reference implementation. The actual thing.
Five operational layers
- CRM & lead routing The system of record for relationships, with automated enrichment, routing, and follow-up scheduling. The CRM you have, doing what it should have been doing the whole time.
- Prospecting & outreach List building, segmentation, sequencing, personalization, and reply handling. Top-of-funnel that runs without someone working a list every day.
- Scheduling & meeting prep Calendar coordination, intake form auto-fill, pre-meeting research and briefs. The work an EA does, done before the meeting starts.
- Analytics & reporting The numbers leadership actually looks at, built from the data the rest of the system is already producing. Live, trustworthy, and explained.
- Operational layer The glue. Alerts when something breaks. Kill switches when something goes wrong. The audit trail that lets you trust the system to run on its own.
Four specific outputs
Working Stack
All five layers deployed, integrated with your existing tools, running end-to-end in your operation. Not a prototype. Not the “phase one” of a longer plan.
Ninety-Day Operator Retainer
I’m inside the system for ninety days post-deploy — running it, evolving it, watching adoption, fixing the things that surface only once the team is actually using it. Bundled in. Not a separate SOW.
Documentation & Runbook
How the system works, why each piece exists, how to modify or extend it. Written for the team who’ll own it on day ninety-one.
Adoption Layer
The part every AI vendor skips. Training, internal champions, friction-spotting, the iterative tweaks that make the system the way your team actually works — not the way they have to remember to work.
Three situations where the Productized AI Stack is right
Good fit
- You’ve seen what an agent-driven operation looks like and you want one running in your business without negotiating scope from scratch.
- You have the organizational capacity to absorb a twelve-to-sixteen-week engagement with active participation from your team.
- You want the system, the operator retainer, and the adoption work in one engagement — not three separate vendor relationships.
Not a fit
- You only need one piece. Look at the Build Sprint instead.
- You’re not sure what your operation actually needs. Start with the Seam Audit.
- You have a working stack and you need someone to keep it running. That’s the Operator Retainer.
Want the whole thing?
Book a 30-minute call. Tell me about your operation, your team, and what you’ve already tried. We’ll figure out whether this is the right shape and what fit looks like.
Book a 30-Minute Call