Engineering and Artificial Intelligence applied to the operation
Invisible rework, brittle integrations, single-vendor dependency, data nobody audits. None of it shows up in your costs by name: it shows up melting your profit. We find it, quantify it, and shield it.
Four weeks. Fixed scope, fixed fee.
Global practice
Our international practice is operational, not decorative: we take on problems in industry and in commerce that have already survived a vendor, an internal project and a spreadsheet. Data that will not talk between systems, a process that exists only in the memory of whoever runs it, an asset nobody can measure, a decision stuck because the number never closes. We build the whole solution on top of that, with artificial intelligence, automation and industrial software under one technical accountability, and we stay until the result shows up in the number your operation is held to. We do not deliver a recommendation: we deliver the system running.
São Paulo
Miami
Lisbon
London
Some of the operations that trust our capability
In five years fixing mid-market operations, we keep finding the same four patterns across completely unrelated industries. All four have a technical solution, and none of those solutions is a report.
Someone knows why that process works the way it does. Someone fixes the spreadsheet before closing the month. Someone solves with a phone call what the system cannot. You know their names. And you know that if two of them leave in the same quarter, the operation stalls.
The cost with no nameUndocumented critical knowledge is an unprovisioned liability, and it always comes due at the worst possible moment.
Three departments bring three different numbers to the same Monday question. Nobody is lying: each pulled from a different place. So the million-dollar call gets made on the instinct of whoever has been there longest, not on the data. And the next meeting opens by arguing which number is right instead of what to do.
Operational efficiency stops being a wishHalf an hour of board time spent reconciling spreadsheets, every single week, relentlessly, all year long, and the decision that stalled is still waiting for consensus.
The half-implemented ERP. The module nobody uses that still shows up on the invoice. The integration only one vendor can touch. The system that has been getting replaced next year for four years. You have genuinely invested in technology, and the net feeling is being more locked in than before.
Business performance matched to operational realityLicences paid without use, single-vendor dependency, and the opportunity cost of the next investment. The challenge is to value what already works and not be swayed because the last vendor disappointed.
The plant grew by addition. Every refit, every new machine, every workaround solved on a Saturday entered the operation and never entered the drawing. Today nobody knows precisely what exists on the shop floor. And every modernisation, automation or certification decision starts with weeks of survey work that should have taken days.
Standardisation, and an innovation culture measured by resultsEvery new project pays the same discovery bill from scratch, every single time. The risk of intervening without knowing what will turn up never appears in the budget until the day the problems blow up.
A vendor is paid to deliver their part. We are driven to answer for the whole, from the plant drawing to the number your operation demands.
The world did not get complex gradually: it got complex all at once. Systems that do not talk, data nobody trusts, decisions made on the instinct of whoever has been there longest. Meanwhile the market demands startup speed with multinational governance. Most companies respond by buying more technology, and buy more chaos with it.
We were born in industry. We spent years drawing layouts, sizing assets and building systems that carry critical operations across several countries, and it was in industry that we learned the most valuable lesson of our history: the problem is almost never where the vendor points. So we do not treat Artificial Intelligence as magic, or as a trend. We treat it as engineering, a discipline where every model has an owner, every automation has a budget line, and every decision carries a return hypothesis that can be audited. AI that does not move a number in your operation is not innovation. It is expense with a good story.
That is what FactoryMind delivers today. We do not choose between thinking and doing, because you cannot: a thesis that never reaches the plant floor moves no number, and work on the plant floor without a thesis only accelerates the error. Consultancies do not draw plant layouts. Integrators do not make the case to a board. We draw the layout, model the asset, integrate the protocol, train the model, and sit on your side of the table when the board asks what it returns. That is why we can answer for the whole result, and that is why we say “do not invest in a retrofit” when your operation calls for a different strategy, one built around your customer and your standard of quality.
We came from industry. We stayed for the thinking.
And we take it back to industry.
Cognitive Transformation
We do not sell hours and we do not sell slides. We sell the clarity that precedes the investment, the engineering that materialises it and, when you want it, delivery with part of our own money in the game.
Design and build
Decide before you spend
Reliable documentation is not bureaucracy. It is what lets you intervene without discovering the plant halfway through the job.
From problem to system in operation
The diagnostic is not the product: it is what stops the build from starting in the wrong place. Fixed scope, fixed timeline, published schedule. What comes out is an executable technical plan, and whoever executes it can be our engineering, your own team or another vendor. The plan is yours either way.
Executive and process-owner interviews, indicator review, mapping of systems and live contracts. We listen before we opine.
You receive: a critical process map and a real technology inventory, almost always different from what the company believes it owns.
4h executive + 6h managersWe quantify where margin leaks: rework, cycle time, brittle dependencies, untrusted data. Numbers, not impressions.
You receive: a Digital Maturity Diagnostic scored by dimension and benchmarked against sector peers.
2h validationWe weigh financial impact, effort, risk and data density to separate genuine AI opportunity from expensive fashion.
You receive: 5 to 8 initiatives ranked by EBITDA impact, with what not to do explicitly flagged.
3h board workshopWhere to start, what it costs, what it returns, how long it takes, and what the plan is if it fails.
You receive: a one-page Value Thesis for the board, a technical dossier for operations and a 12-month roadmap.
2h presentationIt is the cheapest commitment you will assess this quarter, and the only one whose final product is useful even if you decide not to continue with us.
The figure agreed at signature is the figure on the invoice. There is no diagnostic change order.
We do not resell licences, we take no vendor commissions, and we do not recommend platforms we are commercially partnered with. When the recommendation is “do not invest yet”, that is what the report says.
The IP of the diagnostic is yours. You can take it to any vendor, including a competitor of ours, without asking us.
Schedule and your team’s hours are set in week zero. If we overrun, we absorb the cost.
Before any proposal there is a working session with a partner on your specific problem, and out of it comes a written one-page technical opinion: what can be built today, what cannot yet, which data is missing to close the case, and the order of magnitude of the effort.
And if the full four-week diagnostic turns out to be necessary, what you invest in it is credited in full against the project that follows. The assessment stays free either way: it cannot depend on a signature, or it stops being an opinion and becomes a sales instrument.
One senior partner per assessment, and limited slots per quarter for the full diagnostic.
High-complexity sectors
OEE, traceability, OT/IT integration and in-line computer vision. An environment where an hour of downtime has a known price, and where AI has to prove value within the shift, not on a slide.
Routing, demand forecasting and end-to-end visibility across chains with dozens of links and incomplete data. We optimise decisions under uncertainty, not attractive reports.
Traceability requirements, environment segregation, data sovereignty and full auditability. It is the most rigorous discipline we know, and it is the standard we apply as standard.
Scale, learning-path personalisation, privacy law over sensitive minor data, and dropout as a revenue metric. AI here moves retention, which moves cash.
The list exists for a practical reason: projects that cross disciplines usually die in the joints between vendors. When the disciplines sit under one roof, the joint is our problem, not yours.
If our engineering meets defence-sector traceability requirements and carries operations across four countries, your operation sits inside our safety margin, not at the edge of it.
Movement nobody measures is waste nobody corrects.
Hard proof
Clients who authorised it are named. The rest require confidentiality, so we describe the case and not the brand. Every figure is confirmed by the client. Use the arrows to move through all seven.
In none of the seven cases did anyone deliver only their own part. A drawing without integration is just paper. Integration without process is automated rework. AI without trustworthy data is expense with a good story. The gain appeared because one house answered for the whole.
The standard
A real technical problem crosses disciplines: it starts in data that will not talk, runs through a process nobody ever drew, touches an asset with no measurement, and ends in a decision nobody can defend. Anyone who does only one of those parts delivers their part and hands the problem back assembled. We build the whole solution, with artificial intelligence, automation and industrial software under one technical accountability, and the execution standard does not change from project to project.
We have no platform to push and no licence to resell, so the architecture of the solution comes out of your problem and not out of our inventory. Where AI solves it, AI goes in. Where what is missing is instrumentation and protocol integration, that is what goes in. Where drawing the process and connecting two systems you already own was enough, that is what we do, and we say so even when it pays us less. The scope is the size of the problem, never the size of our appetite to sell.
Every FactoryMind mandate has an accountable senior partner in the room with your executive team, not an account executive with a specialist on the phone. Our minimum bar to run a C-level session: proven experience building and sustaining critical operations, not just advising on them. Whoever sits with your board has answered for an operational result before.
A vendor sold on the figure of one specialist transfers you a risk that is not yours: that the person leaves mid-course. Here the mandate is carried by the firm. Squad composition may evolve through the project; accountability for the outcome, the documented memory of every decision, and the standard of engagement do not. Nothing holding your project up lives only inside somebody’s head. That is precisely the problem we solve for our clients; reproducing it would be incoherent.
Architecture, prioritisation and delivery follow the same discipline on every project: declared data sources, explicit return hypotheses, documented decision criteria, and code handed over with the documentation another team needs to take it on. Which means what we build can be challenged, reproduced and verified by third parties, including your own auditors. A vendor that will not expose its reasoning is selling opinion, and a vendor that will not document what it shipped is selling dependency.
In the first conversation, ask to see the criteria and a system in operation, not the CVs. We will show you how we prioritise, what we discard, why, and what the client started measuring after delivery. It is the only honest way to assess a technology vendor before hiring one.
Intelligence
What follows is the material we hand to the boards we work with. It is open because our advantage is not the information: it is the ability to apply it to your operation.
One page, twelve questions, no mention of FactoryMind. If the project does not survive the twelve, it should not be approved.
The decision tree we use: real maintenance cost, vendor-dependency risk, data density, rewrite cost. In most mid-market cases, integrating beats replacing, and we explain why.
A sector diagnostic built on the patterns we find repeatedly. Each point with a way to measure it and an order of magnitude for the impact.
This is the Technical Feasibility Assessment, and it is not a sales call. Thirty minutes of work with a senior partner on your operation, followed by a written one-page opinion: what can be built today, what cannot yet, and which data is missing to close the case. At no cost, and the opinion is yours even if you never hire us.
Write two lines about your operation. We reply within one business day with two time slots. The session is run by a partner, not an account executive.
In the meantime, two pieces that tend to be useful before the first conversation:
