AI agent trained for crypto rails

An expert agent you can work with on call for on-ramps, stablecoin and remittance.

An AI trained on the work of operators who have run it. It decides the way they would, and hands you one 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.

See it answer

Put it the three things you would put to a person.

Talk to it the way you would talk with an expert. Real answers on a real teardown; the reasoning under the first is held back on purpose.

Tap a question to jump to it.
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 on our operators’ own experience, so what comes back is their judgement, not a search result. It rarely needs one: reaching 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.

See it work
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 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.

Get started

Sign up with one live decision.

  • An expert agent, trained on operators who have run this market.
  • One head you talk to, on call at any hour.
  • A named operator behind it, for the question only a person can take.

Bring a decision you are weighing this week. It works the problem the way the operators would and writes up a call your team can act on and live with, one that moves the business. The first conversation is a call, not a checkout.

FAQ

Questions we get.

Because the model is the cheap half. What decides the answer is what it is reading. Here that is what operators wrote down about deals nobody published: what a counterparty accepted, what a fee carried, what failed. Then it is pointed at your numbers, not at the category.

Software, nearly always, and it says so. It answers from the experience of named operators who have run this, at any hour and as often as you like. When a question turns on what somebody did in a room, it stops and hands you one of them.

Give it a flow you already understand and see whether it finds what you found. Put a decision you have already taken to it and see whether it argues your side. It refuses to invent a figure it has not been given, so the places it says it cannot check are the ones worth reading first.

It is saved to your file and it stays yours. Every workstream, note and decision is fetched against your account and cannot be read from another one; we do not share it, and nothing you bring is ever used to train anything. The practice is small enough to name the people who can see it, which is us.

Push back on it. That is what the chat is for, and the recommendation gets argued, not repeated. Nothing here decides on your behalf: a decision is written up as yours, taken on advice, with the reasoning under it and the conditions that would end it. Your engineer acts on your leadership's call, not on a chatbot's.

One decision, start to finish, is €6,000: half on signature, half when the decision lands. If you would rather run it continuously than decide one thing, it is €2,500 a month. Neither of those is the first conversation.

In your corridor, that is a fair thing to ask, and you should ask it early. The practice runs at a few clients at a time, by arithmetic and not policy, so the honest answer is a name and a date, not a promise.

Anything not on this list is worth thirty minutes. and you will get the same answer you would get here, only faster.