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§ 02 · Services · Five pillars · One root
01 / AI 02 / DATA 03 / SOFT 04 / FLOW 05 / SEC
01 / AI

AI
Adoption.

AI that actually does the work. Built on your data. Plugged into your day. No demos that go nowhere.

§ 03 · What this is, concretely
FOUR WORKED PATTERNS
  1. 01
    Operations copilots

    A chat surface that reads your real systems, drafts the answer, and links to the source. Useable on day one, not after a six-month rollout.

  2. 02
    Internal RAG

    Your docs, tickets, transcripts, and notebooks become a single answerable corpus. Citations baked in. Authorisation respected.

  3. 03
    Agent in your existing CRM

    Triage, follow-up, and next-step generation inside HubSpot, Salesforce, or whatever you’re already paying for. No new tab.

  4. 04
    Production-grade models

    When fine-tuning or self-hosting is the right call, we draw the line — not when the demo demands it.

§03B Pricing

TWO DOORS. NO LOCK-IN.

Build one AI capability outright, or run AI as a managed service. Same models, same plumbing, two commercial shapes.

Same pricing on every pillar
01 / Custom Products You own it
From $1,500

Fixed-scope build. You own the code, the data, and the infrastructure. 50/50 deposit and delivery. One-time engagement. No upper band. A discovery call defines the scope.

What you walk away with
  • Source codeIn your repo. Your name on the license.
  • InfrastructureIn your cloud account. Your billing, your control.
  • Handoff docA runbook your next dev can read on day one.
  • Off-rampWritten before the on-ramp. No exit fees.
Let’s get you fitted
02 / Managed Services We run it
From $150 / mo

We run it. You don’t. Monitoring, sync, dashboards, reporting, and the patches when a vendor changes an API. Month to month. Cancel any month.

What runs while you sleep
  • MonitoringIf it breaks, you hear it from us first.
  • Patches & upgradesVendor API changes, library bumps, kept current.
  • Monthly digestWhat ran, what changed, what to watch.
  • CancellationOne month notice. No claw-back. Code stays yours.
Let’s get you fitted

Both doors include scoping. Neither requires a multi-year commitment. Same operators behind both.

§ 04 · The number that governs this pillar
95%

of AI pilots never reach production.

Source Voice of the Enterprise Enterprise AI deployment study
Why this pillar exists

Most of these pilots don’t die because the model is bad. They die because the data underneath wasn’t ready and the workflow on top wasn’t defined. We start with both. The pilot stops being a pilot.

See the full research picture
§ 05 · Proof in the field
ONE ENGAGEMENT · SAME ROOT
Print Services · Commercial Marketing

A sales pipeline, built in nineteen days.

A seven-phase sales workspace built inside MMP Toledo’s existing CRM. Structure first; then the model is just answering questions inside a system the team trusts.

This engagement addressed 95% of AI pilots never reach production — Voice of the Enterprise
19
Days kickoff to demo
7
Sales lifecycle phases
EngagementMinute Man Press Toledo · T-Lock Fusion Platform
PillarsIntegration · Workflow · AI
§ 06 · Frequently asked
FOUR QUESTIONS · STRAIGHT ANSWERS
Q.01 What does “production” actually mean for AI?

It runs every day, on your real data, inside a workflow someone owns. It has monitoring, an off switch, and a person who answers when it’s wrong. If any of those are missing, it’s still a pilot.

Q.02 Why do most pilots fail?

Three reasons, in this order: the data isn’t clean enough to answer the question; nobody owns the workflow the AI is supposed to slot into; and the org doesn’t have a place to put the AI’s output. We fix all three before we touch a model.

Q.03 Do you build new models or use existing ones?

Default: existing frontier models behind your data. Fine-tune when there’s a real reason — domain language, latency, cost, or compliance. We draw the line where it earns its complexity.

Q.04 What’s the typical timeline from kickoff to running?

Two to six weeks for a first useful surface, depending on how clean the data is when we start. Faster if your warehouse is in shape; longer if we’re cleaning house first.

Why this matters See the cost of knowledge loss →

If this is the pillar that fits the symptom, we should talk before the next quarter starts.

Architecture, not apps.

Let’s get you fitted → Read the research