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Custom AI solutions

Eleven AI systems we build, most of them running our own company.

Each one is described the same way: who it is for, what it does, how it is built, what a person still approves, where we run it ourselves, and what it costs. No workshop, no slideware.

The short version

The question every buyer asks and most vendors dodge.

"What would AI actually do for us?" deserves a list. This is the list: eleven systems with a page each, built the same way our own company is run. 9 of the eleven are in production at Strataigize today, and the two that are not say so on their own pages rather than borrowing proof from the others.

If you have not yet decided what to build, start with AI consulting, which is the first two weeks of every build sold as a standalone audit. If you know the workflow, the AI agent development page describes the engagement, and the pages below describe the thing you would get.

The catalogue

Pick the workflow.

How every one is built

Four rules, no exceptions.

Gartner expects more than 40 percent of agentic AI projects to be cancelled by the end of 2027, for scoping, measurement and governance reasons rather than modelling ones. These four rules are the scoping, the measurement and the governance.

01

One bounded workflow

A system is scoped to one job with a clear input and a checkable output. The platform, if there is one, comes from stacking workflows that proved out, never from buying it first.

02

Evaluation before time saved

A hand-labelled set of your real leads, documents, tickets or images is agreed first, and the system is measured against it before anyone claims an hour saved.

03

A person approves the irreversible

Refunds, sends, budget moves outside bounds, records written to a system of record: each starts behind a human step, and the approval rate decides when the step can move.

04

Logged and reversible

Every action carries its reasoning and can be undone. Anyone on your team can read why the system did what it did, and revoke its access in minutes.

Who builds them

Research on one side, production on the other.

Every system is signed off by two people: the scientist who decides what a model can and cannot be trusted to do, and the operator who has run bounded automations on live client accounts every day since 2022.

Government and public sector

Mapped to the way departments buy.

Public Services and Procurement Canada buys AI through its Artificial Intelligence Source List, which sorts AI into three categories by business outcome and qualifies suppliers in bands by contract value. Every system here falls in one of the three categories, and our public-sector page covers the rest of what a review will ask: the Directive on Automated Decision-Making, the Algorithmic Impact Assessment, Canadian data residency and a Canadian supplier.

How we build AI systems for government.

Price

Published, not gated.

Every build starts with a $7,500 AI Opportunity Audit over two weeks, credited toward the build if you proceed. A pilot is one bounded workflow on your real data over 30 to 90 days at $25,000 to $60,000 fixed, with a written success metric and a kill threshold. Running a system in production is a retainer from $8,000 per month, which covers monitoring, maintenance and expansion. Enterprise programs carrying security review and compliance run higher, and the ad optimization system runs inside our paid media retainers.

The full list is on the pricing page. Bring a competitor's quote to the call and we will tell you whether it is fair.

Questions

Custom AI systems, answered.

What is a custom AI solution?
A system built around one of your workflows rather than a product you subscribe to: it reads your data, follows rules your team wrote, acts inside your systems, and is evaluated against your own examples. The model is the smallest part. The integration, the evaluation set and the governance are where the work is, and where the value holds up.
How do you decide which system to build first?
The $7,500 AI Opportunity Audit inventories your workflows, prices each one by hours times frequency, and ranks them by payback and by risk. The first build is usually an internal, repetitive, rules-heavy workflow that touches several systems, because those return more than a customer-facing chatbot and fail more safely.
Do you build on OpenAI, Anthropic or open models?
Per workflow. Our own agents in production run on Claude, and how we work on Anthropic's stack has its own page. Some workflows are better served by a smaller or open model, and some data cannot leave your tenancy at all. The audit names the model for each workflow and the reason, and you own the prompts, the code and the evaluation set either way.

Teams that hand us the number

  • Podz logo
  • Crush Crush logo
  • Kleo logo
  • Backroad Mapbooks logo
  • GameGo logo
  • ZivTrack logo
  • Sad Panda Studios logo
  • Appomate logo

Audit $7,500, pilot builds $25K to $60K fixed, production retainer from $8K per month

Real ranges, published. Ad spend stays in your own accounts.

See the full pricing table →

Where this fits: see the Strataigize Growth System, the ladder every engagement runs on.

Talk to the build team

Name the workflow you want a system to run and we reply within 24 hours with whether it is a fit, which of the eleven it maps to, and the payback math.

Prefer to talk first? Book a 30-minute call instead.

Start with one workflow.

A free 30-minute audit call with the senior team names your highest-value workflow and what it should cost to automate, whether you build it with us or not.

Book your growth audit

Canadian and looking at funding? How the BDC LIFT program works.

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