Strategic Technology & AI Consulting
Invisible rework, brittle integrations, single-vendor dependency, data nobody audits. None of it shows up on your P&L by name: it shows up diluted in margin. We find it, quantify it, and shield it.
Four weeks. Fixed scope, fixed fee.
Some of the operations that trust our engineering
In five years diagnosing mid-market operations, we keep finding the same three patterns, across completely unrelated industries.
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 line on your P&LUndocumented 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.
The cost with no line on your P&LHalf an hour of executive time reconciling spreadsheets, every week, all year, plus the decision that stalled 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.
The cost with no line on your P&LLicences paid without use, single-vendor dependency, and the opportunity cost of the next investment you do not make because the last one disappointed.
A technology vendor is paid to deliver their part. A strategy consultancy is paid to answer for the whole.
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 on the factory floor. We spent years building systems that carry critical operations across four countries, and that is where we learned the most valuable lesson of our history: the code is rarely the problem. So we do not treat Artificial Intelligence as magic, or as a trend. We treat it as strategic 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. Not hands: minds. We sit on your side of the table, next to the person who answers to the board, and we take the role almost no technology vendor accepts, the advisor who wins when you win, and who says “do not invest in this” when that is what needs to be said.
We came from the factory floor. We stayed for the thinking.
Business practices
We do not sell hours. We sell the clarity that precedes the investment, and, when you want it, delivery with part of our own money in the game.
We map where your operation burns margin today and which processes carry enough data density for AI to produce auditable return within 12 months. You leave knowing what to do, what to defer and, above all, what not to buy.
Deliverable: Digital Maturity Matrix plus a prioritised portfolio of 5 to 8 initiatives with estimated EBITDA impact, effort and risk. One page for the board, a dossier for the operation.
4 weeks · fixed scope and fee
We convert business strategy into architecture, roadmap and multi-year budget, sequenced to protect cash and avoid the rewrite that costs three times more later. Every platform decision gets an owner, a date and a number.
Deliverable: target architecture (data, applications, integration and AI), 24-month roadmap by value waves, comparative TCO and a vendor-dependency mitigation plan.
6 to 10 weeks
A senior partner alongside your executive team on a continuous cycle: validating vendor proposals, pricing technical risk before signature and translating technology into board language. Fewer bad contracts signed, fewer decisions made without challenge.
Deliverable: monthly retainer with a fixed executive agenda, independent technical opinions, vendor due diligence and a technology risk dashboard reviewed each quarter.
Monthly retainer · cancel anytime
We take end-to-end delivery (our teams and your existing vendors under a single architectural baton) with part of our fee tied to the agreed targets. If the result does not come, it is not only your problem.
Deliverable: programme governance, architecture guaranteed in contract, orchestrated squads, contractual KPIs and formal knowledge transfer to your team at closure.
Fee + performance (risk-sharing)
The method
Fixed scope, fixed fee, published schedule. At the end you hold a value thesis you can act on with us, with another vendor, or with nobody, and it 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.
Limited slots per quarter, one senior partner per diagnostic.
Hard proof
Our largest clients require confidentiality, so we describe the case, not the brand. The figures are audited by them.
Context. One of the world’s largest food service chains, hundreds of Brazilian locations and a kitchen routine with high staff turnover. Safety compliance was verified by on-site audit: sampled, sporadic and prohibitively expensive to scale.
The real problem. It was not missing policy or missing training: it was the absence of continuous evidence: between one audit and the next, nobody knew what actually happened on the night shift. Accident risk and legal exposure grew inside a blind spot.
What we did. We designed and orchestrated a computer vision layer over the existing camera estate (no hardware replacement), detecting PPE and procedure deviations in real time, with local alerting and an auditable trail per site. The architecture treats images as sensitive data: edge processing, minimum retention, privacy by design.
45%
fewer recordable incidents
107
sites continuously monitored
100%
of the shift audited, previously sampled
zero
spend on new cameras
Context. A chemicals multinational operating across dozens of countries in an environment of extreme regulatory criticality, where a wrong figure does not produce a wrong report, it produces a liability.
The real problem. 12 legacy systems producing divergent truths about the same operation. Indicator close consumed 15 days and ended in manual spreadsheet reconciliation, done by a handful of people, with no reliable audit trail.
What we did. We redesigned data architecture and governance: single source of truth per domain, data contracts between systems, traceable end-to-end lineage and automated quality rules before consumption. No legacy system was replaced: all of them were disciplined.
15 days → 2h
indicator close time
12
systems integrated under unified governance
92%
less manual reconciliation
100%
of critical indicators with auditable lineage
Context. A national reference institution in professional education, at a scale of tens of thousands of students and long-cycle technical programmes.
The real problem. Dropout was measured after the fact. By the time the report named the lost cohort, the revenue had left the cash flow and the student was not coming back.
What we did. We built a dropout-risk predictive model on existing engagement and performance data, wired to a prioritised pedagogical intervention protocol, the human team began acting on a ranked list instead of the whole cohort. AI replaced nobody here: it chose where human attention was worth most.
27
point reduction in dropout
26k
students covered
6 wks
earlier risk detection before withdrawal
4.8x
return on retained revenue
In none of the three cases was the answer to buy a new system. In all three, the gain came from architecture, governance and prioritisation: decisions, not licences. That is what delivering minds instead of hands means.
The standard
Star-dependent consultancies have a structural flaw: quality walks out when the person does. We built the opposite: the method enters the room with whoever enters it, and it is identical in São Paulo, Miami or London.
We do not keep an “AI team” waiting for a project to justify payroll. For each mandate we compose a squad from the disciplines the problem demands, data architecture, process engineering, computer vision, regulatory governance, drawing on our network across four locations. You pay for the competence your problem requires, not the structure we need to sustain.
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 carrying operational accountability, not consulting alone. Whoever sits with your board has answered for an operational result before.
Consulting sold on the figure of one consultant 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 diagnose in our clients; reproducing it would be incoherent.
Diagnosis, prioritisation and governance follow the same discipline on every mandate: declared data sources, explicit return hypotheses, documented decision criteria. Which means our recommendation can be challenged, reproduced and verified by third parties, including your own auditors. A consultancy that will not expose its reasoning is selling opinion.
In the first conversation, ask to see the criteria, not the CVs. We will show you how we prioritise, what we discard and why. It is the only honest way to assess a consultancy 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 not a sales call. It is a working session with a senior partner, about your operation, with a whiteboard and no company deck. You leave with an honest outside read on your biggest risk and your biggest opportunity, 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: