From a prototype that demos well to a system that holds up.
A prototype proves an idea. A production system survives real users, real data, real cost, and the security review. I take AI from prototype to production: the model work, the data and integration layer, the interface, the infrastructure, and the control layer that keeps it all visible and under budget.
- Investment
- From $25k
Fixed or from-X project fee. Scope (systems, data, compliance) sets the band. Complex, regulated, or multi-system builds run $45k to $150k.
All services
Prototypes taken to productionTake an AI prototype to a real system: data, interfaces, infra, and a control layer.
Manual work, automated with control
Support agents you own, not rent
Every lead answered in seconds
Bounded agents that actually ship
Prototypes taken to production
- From $25k
Embedded AI leadership, on demand
The prototype graveyardis full of impressive demos.
Most AI pilots stall in the gap between demo and deployment. The model was never the hard part. The hard part is the data flow, the integrations, the interface real people will use, the cost control, and passing the security review. That is the work that takes a prototype the last mile, and it is the work I do.
- A promising prototype that cannot survive real users or real data
- No interface, no integrations, no cost control
- Stalls at the security and compliance review
- Cost that runs away the moment usage scales
The buildThe full system: architecture, interface, data, and a control layer.
The full system: architecture, interface, data, and a control layer.
Delivery · scope vs velocity
Designed so product, AI, infrastructure, and the business outcome all hold together, and so it passes the review that prototypes fail.
- System architecture and model selection
- Data and integration layer wired to your real systems
- The interface and approval flows people actually use
- A control layer for cost, logs, and quality
- Cloud infrastructure that scales without surprises
A small number of moves,each one verifiable.
Every stage ships its own deliverables, so you can see progress and correct course before the next one starts.
- 01Architecture
We design the system around the workflow, the data, the cost, and the review it has to pass.System design · Model selection · Cost model
- 02Build the layers
Data, integrations, interface, and the control layer get built against your real environment.Data layer · Interface · Integrations
- 03Harden
Cost control, logging, evals, and the security and privacy work that gets it deployed.Control layer · Security review · Evals
- 04Deploy and own
It ships to production on your infrastructure. You own the system and the roadmap.Production deploy · Documentation · Roadmap
Systems that survive the security reviewand run in the real world.
The difference between a prototype and a production system is everything around the model: the data flow, the interface, the cost line, the logs, and the review. That is where I spend the work.
I do not advise on AI from the outside. I build these systems in my own products first, live with the failure modes, and rebuild the parts that break under real users. The patterns I bring to your build are the ones I have already paid for in mine.
See the things I have built
See the things I have built
One scoped fee.No surprises.
Fixed or from-X project fee. Scope (systems, data, compliance) sets the band. Complex, regulated, or multi-system builds run $45k to $150k.
A scoped production system: architecture, build, control layer, deploy.
Multi-system, data-heavy, or regulated builds sit higher in the band.
Before you reach out
Start with the AI Systems Intensive.
$5,000, one focused engagement to map the work and decide what to build. The fee credits into the build. If a build is wrong for you, I will say so and you keep the plan.
Start with a short call. Straight answer either way.
We confirm fit, scope the work, and decide whether to start with the Intensive or go straight to the build.
One letter, every Sunday.Working systems, not hot takes.
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