AI Operating Model.

AI moved tech from something you buy to something you build. We help you in this transition.

This is for you if...

You are building your business on infrastructure someone else owns.

Every change goes through a vendor ticket. Your roadmap is in someone else's hands.

You are paying for capability you do not own and cannot modify when you need to.

Your competitors are building internal capability. You are still negotiating contracts.

If your vendor raised prices tomorrow or shut down, you would have no real option.

What you get from an operating model engagement

Vendor exit plan

What you currently depend on, what it would take to leave each one, and the order to do it in.

VendorCostExit toWhenPriority
OpenAI GPT£8k/moFine-tuned OSS modelQ3high
HubSpot AI£2.5k/moInternal lead scorerQ4med
Ironclad£1.2k/moCustom parserQ2high
Grammarly Biz£0.6k/moClaude APIQ1low

We run a full audit of your vendors and platforms, with the real cost and the switching risk written next to each dependency. This will help you decide what to keep and what to cut or rework.

Internal operating model

How the tech, data and AI work operates once it is yours: who does what, on what cadence, and where decisions get made.

Your IP & proprietary dataOwned datasets, competitive advantage
yours
Internal fine-tuned modelsDomain-specific, trained on your data
yours
Orchestration & tooling layerWorkflows, agents, integrations
yours
Foundation modelsCommodities: OpenAI, Claude, Llama
vendor
Cloud infrastructureRented compute: AWS, GCP, Azure
vendor

We define a clean, AI-enabled team operating model tailored for your business and goals. We define the routines that keep things running week to week, and the escalation paths for anything needing a decision.

Build and run playbook

How your tech gets built, released and kept alive in your business, from the first idea to the launch and beyond.

Setup
Audit vendors
Define ownership
Build
Internal models
Orchestration
Deploy
Prod hardening
Monitoring
Scale
Hire team
Expand capability

We define how something gets scoped and tested before it goes live, what has to be true for it to ship, and who keeps it working afterwards.

Capability and hiring roadmap

The skills you need in-house to run this, which of them you already have, and what to hire for.

ML EngineerMissinghireQ2
MLOps EngineerPartialtrainQ1
Prompt EngineerMissinghireQ1
Data EngineerPresent—-
AI Product MgrMissinghireQ3

We help you hire, train, or outsource the key roles needed for your business to become AI-enabled.

Case study

Built AI-first tech stack after being ghosted by the tech vendor

Short-term rental operator, 100+ properties

5xshipping speed after the vendor left

A short-term rentals platform built their tech stack with a vendor that became unresponsive. We stepped in as fractional CTO and stood up a lean AI-enabled engineering team from scratch, with strong processes for prioritisation, coordination, and delivery. The team now ships five times faster than the vendor did, at lower cost, on infrastructure the company actually owns. New features now are built in a day, instead of a couple of weeks.

What changed

  • New features often shipped in less than 24h
  • Employees now are happy to work with tech, instead of fighting it
  • Core stack owned in-house at lower monthly cost

How we help you.

Start with a free call. From there we either run a full value iteration on your stack and hand you the plan, or we stay on as your fractional CTO for data and AI.

  • Checkpoint

    Free, 30 minutes

    Bring one thing that's stuck. We tell you what's wrong with it and what to do first. For free.

    Book a checkpoint
  • Value Iteration

    Scoped engagement, one-off

    We analyse your whole stack and build a pragmatic plan: what's broken, what to fix first, and who should own it. Your team or any vendor you hire can run it.

  • In the Loop

    Ongoing, fractional

    We work with you for a few hours weekly to push the strategy with e.g. prioritisation, vendor calls, architecture decisions and hiring.

Questions we get asked.

Your AI capability is something you own rather than rent. Your data is not locked in vendor platforms, your workflows are documented and portable, and your team can operate and evolve the systems without calling a vendor every time something needs to change.

It becomes one when pricing changes, a vendor shuts down, or a competitor builds the same capability in-house for less. Vendor dependency is comfortable until the vendor's interests diverge from yours.

With a vendor audit: mapping what you depend on, what is replaceable, and what the real cost and risk of each dependency is. Then we sequence the exits so each one moves you toward something better. Cutting cost on its own is not a good enough reason to move.

Not necessarily. Owning your stack means understanding and controlling your systems, not building everything from scratch. We design the operating model to match your actual team size, so you are not hiring for capability you do not need yet.

Our part is a few weeks: the vendor map, the operating model, and the sequenced exit plan. Running that plan is your team's work. Most businesses see meaningful progress in 3 to 4 months, and full independence on core systems is usually 6 to 8 months out.

Let's get started.