AI production systems

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.

InvestmentFrom $45k

Fixed or from-X project fee. Scope (systems, data, compliance) sets the band. Typical builds run $75k to $150k.

The problem

The prototype graveyard is 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.

Where it hurts
A promising prototype that cannot survive real users or real dataNo interface, no integrations, no cost controlStalls at the security and compliance reviewCost that runs away the moment usage scales
What I build

What you get, and how it is built.

The build

The full system: architecture, interface, data, and a control layer.

Designed so product, AI, infrastructure, and the business outcome all hold together, and so it passes the review that prototypes fail.

Included
System architecture and model selectionData and integration layer wired to your real systemsThe interface and approval flows people actually useA control layer for cost, logs, and qualityCloud infrastructure that scales without surprises
How it works

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.

01

Architecture

We design the system around the workflow, the data, the cost, and the review it has to pass.

System designModel selectionCost model
02

Build the layers

Data, integrations, interface, and the control layer get built against your real environment.

Data layerInterfaceIntegrations
03

Harden

Cost control, logging, evals, and the security and privacy work that gets it deployed.

Control layerSecurity reviewEvals
04

Deploy and own

It ships to production on your infrastructure. You own the system and the roadmap.

Production deployDocumentationRoadmap
Why me

Systems that survive the security review and 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.

Pricing

One project fee. No surprises.

Fixed or from-X project fee. Scope (systems, data, compliance) sets the band. Typical builds run $75k to $150k.

Build
From $45kscoped

A scoped production system: architecture, build, control layer, deploy.

Full architecture + buildInterface + integrationsControl layer + deploy
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Typical range
$75k-$150k

Multi-system, data-heavy, or regulated builds sit higher in the band.

Multiple systemsHeavier data workCompliance
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FAQ

Before you reach out

Next step

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.

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One letter, every Sunday. Working systems, not hot takes.

Build logs, working systems, and field notes from running a portfolio of AI ventures. Sent weekly, never more.

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