Operator-trained AI for crypto rails

An expert you cannot hire. On call, for on-ramps, stablecoin and remittance.

An AI trained on the work of operators who have actually run this. It decides the way they would, and hands you one of them when only a person will do.

Whale merchant pricingReturning-user pre-selectionPerceived-value pricingFX and currency captureSpeed pricingCorridor mixShare of checkoutTier gating at checkoutWhale merchant pricingReturning-user pre-selectionPerceived-value pricingFX and currency captureSpeed pricingCorridor mixShare of checkoutTier gating at checkout
Wallet listing termsMessenger-scale merchant dealsRecovery flowsQuote segmentationCheckout step orderVolume-based economicsGas selectorNever lose a transactionWallet listing termsMessenger-scale merchant dealsRecovery flowsQuote segmentationCheckout step orderVolume-based economicsGas selectorNever lose a transaction
It has priced this corridor before.

Fifteen years on the record: every optimisation he shipped, why it was tried, what it cost, what moved.

Team spotlight

Our operators are highly experienced.

Omar Ben Hachme is a senior product and growth operator of fifteen years, eight of them in payments. He took a top-three European on-ramp from roughly $180M to about $1B annualized and built the value-based pricing this category now argues about.

The answers come from the chat, at any hour and as often as you like. It is an AI trained and fine-tuned on our operators’ own experience, so what comes back is their judgement rather than a search result. It rarely needs them: escalation to an operator is the exception.

Omar Ben Hachme
Trained on the work of
Omar Ben Hachme
On-ramps
Track record

What it was trained on.

Every desk is built from operators who have run it, their experience written down, and an AI trained on that. This is the work it came out of.

Omar Ben Hachme · Mercuryo
A top-three European on-ramp taken from roughly $180M to about $1B annualized
Rasmus Fahlander · Klarna
Led the checkout carrying $20B+ a year — more than one in five Nordic e-commerce checkouts
Daniel Sneijers · Uber
Decides which payment methods Uber's riders are offered, and in what order
Rasmus Fahlander · Kustom
Klarna Checkout carved out into a standalone company, now serving 20,000+ merchants
Daniel Sneijers · Adyen
Knows how acceptance rates are won, from inside one of the largest acquirers in the world
Omar Ben Hachme · Mercuryo
Signed the wallets and messaging apps that put a ramp in front of millions of users
Working with it

You work with it the way you would work with a real expert. Bring it the thing you are stuck on.

It is one head, not a menu. Flows, pricing, merchants, and which part of your integration to fix first.

01

Walk it through your flow

Give it your onboarding, your checkout, a screen recording. It reads what happens in the flow, against your own numbers.

02

Take the pricing apart with it

Pricing, share of checkout, recovery, FX capture, speed. It works out what a fee can carry and shows you the working.

03

It says which one to do next

Several things are open and only one can have the week. It ranks them on what each changes about your position, not on which is newest or largest.

04

Rehearse the merchant pitch

Before the call: how the deal gets framed, what the counterparty will accept, and where you are about to overreach.

05

Leave with a decision your team can act on

A written record of what was decided and why, that an engineer can act on knowing it is their own leadership's call, taken on advice.

06

And a person, on the rare question that needs one

Almost nothing leaves the chat. When something turns on what a counterparty did in a room, it says so and an operator picks it up.

Against a general model

A general model has read everything. It has done none of it.

Same interface, entirely different thing underneath.

Where it learned thisEverything ever published about paymentsWhat operators did, inside the companies that did it
What a merchant will acceptInference from public write-upsThe deals we sat on the other side of
What a number should beAn average of the open webFigures we have seen carry, and the ones that did not
What goes wrongThe success stories — the only ones written downThe failures, which nobody publishes

Put the same situation to both, side by side.

Run a live decision through a frontier model and through this, in the same hour. We would rather you ran that than took our word.

See it work

What it knows that a model does not.

One workstream, end to end: the mechanisms, the ratios that survived negotiation, and the exclusions that stop a good idea costing you money.

Get started

Sign up with one live decision.

Bring something you are actually deciding this week. You will see what it is worth to you before anything is agreed.

  • Thirty minutes with an operator every month, on top of the chat.
  • A quarterly commitment, so nothing has to be decided fast.
  • Nothing is billed until the first recommended fix has shipped.

Thirty minutes on your decision.

Nothing to sign, and nothing to pay. You leave with an operator’s read on it either way.

Sign up