A state-of-the-art autonomous agentic system, for U.S. plants

First plants at no charge · Applications close 19 September 2026

Was it the market, or was it you?

You get what a data scientist, a planner, an analyst and a finance lead would tell you about your own plant — from an app that runs on your own computers, at no cost, in hours instead of years. The first plants pay nothing. Applications close 19 September; the work starts at the beginning of 2027.

Apply now — it costs nothing See what you get Two minutes. Non-binding. Nothing due now. Nothing to install today — the company is in formation and the build starts at the beginning of 2027.

Is this you

Four problems. They are all the same problem.

Every one of these comes from the same gap: decisions are made faster than they can be measured. Close that gap and all four get easier at once.

Too many decisions, none of them priced

A supplier, a run size, a promise to a customer. Each one moves cash. Nobody can say by how much until the year is closed and it is too late to choose differently.

Then: you see the cash effect before you commit, not after.

Results nobody can explain

Margin fell. Was it input prices, freight, and demand, or was it your sourcing and your mix? Without an answer, next quarter is another guess.

Then: the result comes split into the part you caused and the part you absorbed.

Hours on work that should run itself

The same sheet rebuilt every week. The same reorder judged by feel. The same report retyped for the same meeting.

Then: the small repeating decisions run automatically and you review exceptions.

Data that cannot answer a question

No structure, no versions, no record of what was decided or why. So a result today cannot be traced back to the choice that caused it.

Then: this is the one to fix first, and it is where the work starts.

The idea

One number tells you nothing. Two numbers tell you what to do.

Your margin change is really two changes added together. One part came from outside: input prices, freight, demand, a supplier's own trouble. The other part came from inside: what you sourced, what you ran, what you held, how you staffed it.

Reported together, they cancel out into a single figure you can only shrug at. Pulled apart, they give two different instructions. Volatility you cannot control, you hedge and diversify against. Inefficiency you can control, you fix — and the fix is worth a known amount.

Doing this needs structured data, versions, and a record of what was decided and when. That is why the first work is on your data, not on a slide.

A margin change split into an outside part and an inside part A single bar labelled "the number you see today" sits above a second bar of the same width, divided into a left portion for causes outside the plant's control and a right portion for causes inside its control. WHAT YOU SEE TODAY one blended margin number WHAT IT IS MADE OF outside your control inside your control input prices, freight, demand, a supplier's trouble hedge and diversify sourcing, mix, inventory, run sizes, labour fix, and price the fix
The split is the product. Proportions here are illustrative — yours come from your own data.

The vision

To create the most advanced and secure autonomous agentic system for manufacturing in the world.

Designed for extreme security

Safer than a spreadsheet. An Excel file gets emailed, copied and left on a laptop; this is built so your numbers never leave the building at all.

Architected by people who have done the work

Finance, supply chain, data science and innovation expertise, on state-of-the-art world modelling — not a chat window bolted onto your spreadsheets.

It delivers, and keeps delivering

Chatbots talk. This is designed to do the work: financial and economic modelling that holds up in production, that understands what it is doing, and that shows its workings every time.

America is the greatest country in the world. AMR hopes to make it greater still.

Made by an Italian who loves America — and who came here to build.

A statement of intent, not a description of something finished. None of it is built yet — which is exactly why it is written down here, where you can hold it against what arrives.

What you get

Five things. The first one is the reason to say yes.

Everything below is built to keep working after the Service ends, because a tool you cannot run yourself is just a report with a longer shelf life.

01 · The first Service

One page that says where the next dollar goes.

When a supplier, a product mix, or an inventory level is on the table, you get the cash effect of each option and a recommendation you can defend in a room.

  • Trace each cost or profit back to the decision that produced it, not a blended year-end figure
  • Separate what the market did from what you did, so next year’s plan is not another guess
  • Price sourcing, mix and inventory in cash before you commit
  • Every claim written so you can check it later against your own books

Apply for a free 2027 Service

Layout of the one-page summary A wireframe of a single page: a heading strip, one headline figure, three small tiles, a paired bar chart comparing outside and inside causes, and a recommendation line.

Layout of the summary page, drawn empty on purpose. No sample figures, because there is no client work to show yet.

02

Mix priced in cash before you commit

Sourcing, product mix, and supplier concentration are usually decided on unit price and hope. The Service prices those options from your own numbers, including what concentration is costing you in risk terms, so you can choose before you are locked in.

03

Reporting that carries the financial bridge

The weekly sheet and the meeting pack still run themselves. Each figure is traced back to the decision that produced it, period over period, so the report is an explanation rather than a reprint.

04

A cash policy, designed as one sequence

Purchasing, production and payment timing treated as one free-cash-flow policy rather than three separate habits. The first Service delivers the policy design, the objective function, and the data required to train it — not a trained model on day one.

05

Keep the method

The model, the templates, and the tracking stay with you and work the same way next year. No data-science hire, no dependency on me to run it again.

How it works

Three steps, and an honest answer at step two.

  1. You apply

    By 19 September 2026

    Plant details and a contact, two minutes. Non-binding, and either side can withdraw at any time.

  2. I read it and choose

    From October 2026

    Every application gets read after the window closes. Confirmations to selected businesses go out from October 2026. If the numbers cannot support the work, I tell you that instead of selling you a study.

  3. The work starts

    Beginning of 2027

    The first version is built for your plant, on your numbers, with the savings written down so they can be checked afterwards.

What it costs

Hire five seats in the market. For the first plants, pay none.

A market comparison, not a former price of ours. Left is what five specialists cost. Right is what you pay.

If you hired five specialists

$3,000

15 hours at $175–250/hr. Scoped projects quote from $5,000.

Your cost in this cohort

$0

No card, no deposit, no invoice.

How that $3,000 comparison is built up

Five separate people, $175–250/hr. A short booking each is about 3 hours — you do not buy 90 minutes of a data scientist.

  • Hire a finance analyst ~3 hrs $525–750
  • Hire a supply-chain and operations lead ~3 hrs $525–750
  • Hire a data scientist ~3 hrs $525–750
  • Hire a software engineer ~3 hrs $525–750
  • Hire a process-innovation leadThe plant problems that have no playbook ~3 hrs $525–750
  • Five short bookings 15 hrs $2,625–$3,750

15 × $200/hr is about $3,000. Here those same five seats are software running on your own computers, and your cost is $0 — with nothing spent on handoffs, briefing, or reconciling five separate opinions. Five half-days at $250/hr, or a scoped project, from about $5,000.

The launch cohort is a bet I am willing to carry, not a discount off a former price of ours. For the first plants, the Service costs nothing. If it works and you want a stronger version afterwards, we agree in writing. Nothing on this page promises a result, and nothing converts to a paid arrangement automatically.

There is no second step to sign up for. If the first one works, the numbers will make the case better than I could — and you will be the one deciding what a second engagement is worth.

Applications close 19 September 2026. Applying does not reserve a place, applying early confers no priority, and I may choose fewer plants, or none. Confirmations go out from October 2026. Work begins at the beginning of 2027 either way. No card is collected.

Why you can trust it

Your books never leave your building.

Most tools ask you to upload your numbers to someone else's computer. This one never asks, because it is built so that it cannot use them. Nine questions, answered in one line each.

  • Local only
  • End-to-end encrypted
  • No logs
  • Memory-only model
  • GDPR-ready by design
  • HIPAA-ready by design
  • No subprocessors
  • Nothing retained
  • Where does my data go?

    Nowhere. It runs on your own computers, where your numbers already sit.

    How that works

    The software is installed inside your building and works there. There is no server of mine holding your data, because there is no server of mine in the picture at all.

  • Can you see my numbers?

    No. I never hold the key that unlocks them.

    How that works

    The key is made on your machine and stays on your machine. Without it the files are unreadable noise. I never hold the key, so I could not read your numbers even if I wanted to.

  • Is anything logged?

    No. Nothing records what you opened, asked, or looked at.

    How that works

    There is no usage log to keep, so there is nothing to leak, nothing to hand over, and nothing here for anyone to read later.

  • Where does the AI model run?

    On your own hardware, by default. Unplug the network and it still answers.

    How that works

    If a job would need a model larger than your machine can hold, nothing is sent anywhere unless you switch that option on. If you do, that model is to run in a sealed enclave: memory only, nothing written to disk, no logs, no questions or answers kept, checked cryptographically before the session starts, and wiped when it ends. Either way your numbers never train anything.

  • What is kept, and for how long?

    Nothing of yours. No copies, no backups, no history of what you asked.

    How that works

    This is not a thirty-day or ninety-day retention policy; there is nothing to expire. It also means there is nothing for me to delete on request, and nothing for anyone to subpoena from me.

  • Does this meet GDPR, HIPAA and the rest?

    The design removes most of the question, because nobody else ever holds your data.

    How that works

    Those rules mostly govern what happens when somebody else holds, moves, or looks at your data. Here there is no transfer, no processor to appoint, and no breach surface on my side. Health information is never disclosed to me, so there is no business associate to sign up; export-controlled drawings are never exported. I will not claim a certificate that does not exist yet: the position is to be confirmed by independent U.S. counsel and security auditors before the first plant uses the software. None of this is legal advice about your own obligations.

  • How do I know this is true?

    You do not have to take my word for it — the code will be published.

    How that works

    Open source means you can hire any cybersecurity firm you like and have them read it line by line, then tell you whether what I claim here is what the software actually does.

  • Who checks it before it runs?

    Independent U.S. security experts, not me.

    How that works

    Before the software touches a plant's numbers, it is to be verified and certified by outside experts who have no stake in the answer.

  • How is this different from a cloud tool?

    In the cloud your data sits on someone else's computer. Here there is no someone else.

    How that works

    Whoever runs a cloud service can be compelled, careless, or breached. Treat this like a notepad on your own desk — safer, really, because a notepad cannot tell anyone who opened it.

The rare part is the combination: local only, end-to-end encrypted, no logs, open source, independently certified. Any one of those is common enough. All five together is what turns confidentiality from a promise into a property of the design.

None of this exists today. It is the standard the software is to be built and independently tested against before any plant's data is involved, and the confidentiality duties are written into the conditions you would be signing.

Who does the work

Stefano Ciccarelli

Data Scientist at a Fortune 10 / FAANG company. New York metro, based in Jersey City.

The problem sits across five disciplines rather than inside one, and the Service puts all five in one place.

  1. I
    AI and data science Data scientist at Fortune 10 / FAANG in New York; top grades in the Oxford University and Imperial College AI specializations
  2. II
    Finance and analytics Double master’s degree, cum laude, across three European universities
  3. III
    Supply chain and operations Winner, 2025 Big Tech internal EU Supply Chain Innovation Award
  4. IV
    Production-grade software development Enterprise-grade software in production at Big Tech on modern cloud infrastructure; zero maintenance overhead, end-to-end encryption for zero-trust requirements
  5. V
    Innovation and non-linear problem solving First or second place in multiple innovation competitions; moved to the United States to scale a system built at the EU headquarters

Why the number can be trusted

Finance training and machine learning, pointed at plant decisions.

Master's in corporate finance, LUISS, cum laude — equated to a U.S. M.S. in Finance.
Warwick and EDHEC: business intelligence, data, finance and risk.
Imperial College London: machine learning, with Distinction. Oxford: artificial intelligence.
Built independently, on public data and my own methods. This work does not use a current or former employer's systems, data, or methods.

Instead of

What the alternatives actually give you.

  • A large professional-services firm

    The same class of work, at a price a $20M plant will not sign, and the model leaves with them when the work ends.

  • Your own spreadsheet

    An accurate record of what happened. It cannot tell you which part of what happened was your own doing.

  • A freight broker

    Can move the crate. Will not tell you whether to change supplier, and leaves you nothing reusable for the next order.

  • An AI vendor or a data-science contractor

    Can build a model. Cannot tell you which decision it should optimise, or what the answer is worth in your accounts.

Why now

Reshoring is being talked about faster than it is being measured.

Talk of bringing work home is up, and imports still rose. That gap exists because most plants cannot price the decision, so they sign on unit price and hope. That is the gap this closes.

$2.93T

U.S. manufacturing output, roughly a tenth of GDP. Federal figures.

35,000+

Small and mid-sized plants in the NIST-MEP universe.

97%

of U.S. exporters are small firms, and they still hold only about a third of export value.

These are counts of how many plants exist and what they ship. They are public figures about the size of the sector, not a claim about how many will buy this.

Later · not part of this window

Tools that go looking for the next market or the next product

  • Screening export markets a plant could serve, and the paperwork path into them.
  • Products a plant could make with the equipment it already owns, and the inputs those products need. Plant goods, not consumer retail.

Not live, and not part of the first 2027 Service. There is a checkbox on the application if you want it noted. It will only be built if plants use the first Service well.

Before you ask

The questions everyone asks first.

Can I buy the software today?

No. Nothing here is live software for sale right now. The company is in formation and work begins at the beginning of 2027. What you can do today is apply to be among the first plants the Service is built for, at no charge.

Am I committing to anything by applying?

No. The application records a non-binding expression of interest. Either side may withdraw at any time, for any reason. No payment is due now, and nothing authorises work or billing before 2027.

How are plants chosen?

By hand, by me, after the window closes on 19 September 2026. I am looking for plants where the question is real and the records are good enough to answer it — not for whoever clicked first. Applying early confers no priority and does not reserve anything. Confirmations go out from October 2026. Everyone who applies gets an answer either way, and if you are chosen you sign the letter of interest on this site to make it official.

My data is a mess. Is that disqualifying?

It is the opposite. Unstructured data with no version history is the normal starting point and it is the first thing the work addresses. What matters is whether enough was recorded to reconstruct past decisions. After a short call you will get a straight answer about that, including "not yet" if that is the truth.

How do I know a saving is real and not a story?

Because the claim is written before the work, in terms your own books can settle, and the market part is separated from the internal part. If a good quarter came from prices moving in your favour, the report says so rather than taking credit for it.

First plants at no charge, chosen by hand. Applications close 19 September 2026.

Two minutes to apply. Non-binding, withdraw whenever you like, nothing due now.

Apply now
Apply — free 2027 Service