Meitheal Partners
MEH-hal · Gaelic: a group who gather to do one job, then go home

Independent advisory · Asia

Build fast. Own what you build.


Your AI runs on infrastructure you don't own. If you wanted to change supplier tomorrow, nobody could tell you what it would cost.

Everyone will tell you what to do with AI. We tell you what it's doing to you.

We look at your IT, your data and your AI, and we show you where it breaks — before it does.

The method

Three questions, every time

A method, not an opinion.

I

Frugal

Is it proportionate? Expensive is fine if it returns a multiple. We help you set the measures and benchmark them, so you can prove the return rather than assert it.

II

Sovereign

Can you still change your mind? Not privacy — reversibility. Whether you can leave, what you would take, what it would cost. And who you need beside you, well outside your own industry.

III

Secure

What are you exposing? Who reaches your data, what vendors may do with it, how much rests on one of them.

Most organisations can tell you what their AI cost. Very few can tell you what it returned.

We don't allege anything about your vendors. We read what you have already agreed to — retention, sub-processors, human review, what survives termination, whether your fine-tuned weights are yours to take — and show you what you cannot get back.

Scope

Three layers, because the problem is rarely where you think

AI Models, agents, the vendors behind them Data Pipelines, quality, ownership, access IT Infrastructure, networks, legacy estate everything rests on it but it shows up here
Most AI failures start two floors down. The model was fine — the data was never fit, or the infrastructure could not carry it at real load.
At the AI layer

We help you choose the right ambition, and the solution that matches it.

At the data layer

We help you build the foundation everything above it depends on.

At the IT layer

We test whether the decisions hold — and name the partnerships you need.

Foresight

Why AI investments fail

Five scenarios, modelled against your numbers, before you get there.

01

The cost wall

Pilot economics that break at production volume. We give you the number and roughly the month.

02

The repricing

Terms change. We read what you actually bought and what position it leaves you in.

03

The supplier

What you built on their model is, from their side, a feature they haven't shipped yet.

04

The load

Where the layer underneath gives out before your AI does.

05

The exposure

What surfaces the day someone asks where the data goes.

Cost Pilot Production the wall
Most AI economics work beautifully at pilot scale. We tell you where the curve turns, and roughly when.

If data is the new oil, you have drilled the well and loaded it onto ships owned by someone else — and you are paying them for the privilege.

Modelled scenarios, not predictions.

The engagement

How it works

01We look

The real estate, not the deck.

02We map it

What you run, what it costs, what moving would take.

03We model it

Five scenarios, your numbers.

04We tell you straight

Kill, keep or fix — with a number on cost and risk.

05We help you do it

With your people, against agreed measures.

Deliverables

What you get

  • A dependency map. Every layer, scored. Yours to re-run each year.
  • Five modelled scenarios. With numbers and timing.
  • A kill list. At least one thing you should stop.
  • A fitness-for-purpose verdict. What to change, in what order, at what price.
  • An IP containment plan. What you are handing to frontier vendors, and how to hand over less.
  • A value baseline. Agreed measures for what good looks like, and a benchmark to track it against.
  • Requirements for your next purchase. So your buyers know what to ask for.

The only AI adviser with nothing to sell you.

Anyone can claim independence. These are the things we will not do.

  • We will never take money from an AI vendor. No fees, no referrals, no reselling.
  • We will never recommend what we wouldn't run ourselves.
  • We will never hand you a review without a kill list.
  • We will never put someone on your account who is learning on it.
  • We will never keep what we build from you. The map, the models, the method — yours.
  • We will never tell you what you want to hear.

We will tell you what you bought, what it costs and what it commits you to. We will not tell you whether it is enforceable — that is your counsel's job. We are technical people who speak business.

In this region

Why this matters here, now

Regulators here are moving faster than most of the world, and on exactly these questions. Korea's framework reaches any business whose AI affects Korean users. Japan is evaluating domestic against foreign models, with control of infrastructure an explicit criterion.

Engagements

Three ways to start

Snapshot — one week Foresight Review — four to six weeks Delivery — three to twelve months
Most clients start at the top and decide from there.

One week

Snapshot

One layer, or the question keeping someone awake. Ten pages and a number.

Four to six weeks

Foresight Review

All three layers. The map, the scenarios, the kill list, the plan.

Three to twelve months

Delivery

We execute alongside your team, with senior accountability throughout.

Fixed fees, agreed before we start.

The practice

Judgement, not headcount

Every engagement is staffed by practitioners who have run these functions, and scaled around the problem rather than around a bench you would end up paying for.

  • Advisory. Technical and business strategy leaders with global experience — data and AI leadership across insurance, infrastructure, energy, government, international development and public-private convening organisations, working with ministries, development finance institutions and some of the largest players in their industries.
  • Security. Serving CISOs, in the room when it matters.
  • Engineering. Senior engineers and analysts across Asia and Europe.
  • In your market. People who are already there, rather than flying in and guessing.

A meitheal is the old Gaelic custom of neighbours gathering to bring in one harvest, then going home. It is how we staff every engagement, and it is why we are named after it.

You get the people who have done it, and none of the people learning on your account.