Index

Origins: Forging a Generational Founding Team Market: It is Just Everywhere Opportunity: Serving the Silent Hero Product: Cracking the Real Pain Scaling the Product: the Tractian way Actionable Insights

Tractian: Brio

Brio. You can find this word on Tractian’s career page. It is one of the core values the company looks for when hiring someone.If you Google the definition, it says “vigor or vivacity of style of performance”. If you ask ChatGPT about it, it says, “‘brio’ is not very used in everyday English, but it appears occasionally in more formal or literary contexts. It means vigor or energy, particularly when describing someone’s performance, style of manner”. This word is a fitting description of the uniqueness of Tractian’s founders: Igor, Gabriel and Leonardo. Contrary to the popular belief that founders should be complementary to each other and cover each other’s weaknesses, these three share strikingly similar traits: a lifelong familiarity with industrial plants, and the relentless energy that fuels their drive to build the company. As Leonardo mentioned to us in a conversation, complementarity may be overrated. The most important thing is if you share the same values and if you enjoy working with the other.

Origins: Forging a Generational Founding Team

Igor’s journey: Self-Taught, Self-Driven

Igor is the embodiment of the classic tech entrepreneur we see in movies: self-taught, relentless, and obsessive. He taught himself to code at just 10 years old. At 13, he had already launched his first entrepreneurial venture: an inventory management system in PHP for a Portuguese manufacturing company. Because of his young age and high-pitched voice, he used to bring his father — gray-haired and deep-voiced — to sit in on commercial calls and handle negotiations on his behalf. From that first project on, Igor knew that his place in the world was to be a builder.

Illustration of Igor and his father

Manufacturing and maintenance have been part of Igor’s DNA from an early age. His grandfather was a mechanic, and his father, a maintenance engineer who spent 25 years working at an International Paper mill. Growing up, Igor was immersed in that environment and exposed to its challenges early on. Like many traditional Brazilian middle-class workers who had lived through the country’s hardships and transformations in the second half of the 20th century, Igor’s father placed great importance on education as a path to success and stability. He insisted that Igor go to college, even though Igor already knew he wanted to build. That decision became one of his father’s greatest contributions to him — it was in college that Igor met his future co-founders.

Gabriel: Brains, Discipline and Defiance

Unlike Igor, who never cared much about formal education and didn’t even plan to go to college, Gabriel was the classic straight-A student every mom asked for: he studied hard to get into top universities, and consistently earned the highest grades. Igor and Gabriel’s friendship took shape quickly in the first weeks of college, as they were classmates. Igor soon began sharing his entrepreneurial projects with Gabriel, and was surprised by Gabriel’s extremely honest and direct approach: if something looked bad, he would say so bluntly, even at the risk of sounding impolite. Gabriel also carried a mix of confidence and defiance, often “showing off” his skills by betting with friends that he could complete tasks faster or better than them. In the first project they worked together on, a crowdfunding platform, Gabriel and Igor were discussing the platform’s design, and Gabriel mentioned he hated it and that he was going to redo it all over again. Igor then asked Gabriel: “Do you understand Photoshop?”. Gabriel said he did not. Igor then said, “Well, good luck improving this design”. The two made a bet. One week later, Gabriel strolled in with a completely redesigned platform that, to Igor’s surprise, looked better than his own, despite Igor’s far greater experience with design tools. This lighthearted, almost innocent story revealed two traits that would later define Tractian’s culture: the founders’ harsh, no-nonsense transparency with one another, and a confidence so strong it bordered on arrogance.

Leo’s Leap: The Salesman Who Completed the Trio

The last piece of the founding trio is Leo. Like Igor, Leo grew up close to the factory floor. His brother worked his entire life with maintenance, and still does to this day. Leo saw the struggle up close. He recalls one Christmas Eve when his brother had to leave the family dinner table because a gearbox had fallen in the factory’s boiler. Leo met Igor during a course at the University of California, Berkeley, where they grew close and began exchanging ideas. Some time later, while working as a Sales Lead in the industrial sector, Leo faced a major problem: a hydraulic pump kept failing, and no one could figure out why. That’s when he remembered Igor once mentioning an idea for diagnosing mechanical failures in factories. Leo picked up the phone and called him. That call led to what would become Tractian’s first client opportunity (though the company didn’t exist yet). Igor and Gabriel went all the way to the industry’s headquarters and pitched directly to its directors. Leo backed them in the meeting… but everything went wrong. Igor went into excessive detail. They priced a product that didn’t even exist as if it were finished. Leo nearly got fired for bringing in two young founders pitching something far from ready.

After the disastrous meeting, Igor called Leo and suggested grabbing a beer at Largo da Batata in São Paulo. The idea was to cool off and forget the pitch. But over beers, Igor got to the point: “Why don’t you come work with us? Gabriel and I are more product people, and we need a salesperson like you.” Leo hesitated at first. He had a good job, steady pay, and the idea was still just that, an idea. But the more time he spent with Igor and Gabriel, the more he saw the potential. Eventually, he realized it was an opportunity he couldn’t miss, and he said yes. In Brazil, we say “o santo bateu” (literally, “our saints matched”) when two people instantly click and form a strong bond. This is what happened between Igor, Gabriel, and Leo — their saints matched. From day one, the three founders have been deeply aligned, bound by complete trust and a rare ability to be brutally transparent with one another. Contrary to popular belief that the great founding teams need complementary opposites, they describe themselves as strikingly similar, almost extensions of each other. This chemistry shaped Tractian’s journey: the company’s strong culture and well-defined values are a direct reflection of the way its founders think, act, and push each other (and the entire company) forward.

Market: It is Just Everywhere

"Your product is just as good as your factory." — Elon Musk

Look around. Nearly everything within your reach began in a factory. The clothes you wear. The shoes on your feet. The table where you sit, the chair you’re on, the phone in your hand, even the device you’re reading this on. Factories, often far from sight, running day and night, are the invisible engine behind modern life. Every new technology, every product we take for granted, only becomes real because somewhere, someone built a new factory to make it at scale, from the state-of-the-art semiconductor foundries in Taiwan, to simple motorcycle assembly lines in Manaus, Brazil.

Factories are the basic unit of production for everything we consume. Like any physical asset, the machines inside these factories wear down and fail. They require constant maintenance to keep production running. But here is the problem: Industry reports show that most technician hours are spent on reactive fixes — responding after breakdowns—while maintenance budgets are drained by inefficient programs that fail to prevent downtime. Several root causes explain why industrial maintenance remains so inefficient:

Trapped in analog: many industrial facilities still rely on analog systems and non-digital equipment.
When machines stop, everything stops (including revenue): machine failures can lead to unplanned downtime that is expensive and crippling.
Fixing machines after they fail is still the norm: maintenance is mostly reactive, relying on manual services instead of predictive approaches.
Misaligned incentives in industrial maintenance: Machine manufacturers often profit from maintenance, creating little incentive to optimize machine lifespan.

Trapped in analog

As mentioned above, Igor’s father spent his entire career in maintenance. He recalls that, in his early days, the only way to learn about a machine’s specifications was by going to the technical archive — a large, dim room in the factory lined with shelves of thick manuals. If a piece of equipment failed, the only way to understand it was to pull down the right binder and read page after page until you found something useful. There was also a more “hands-on” method: listening to the machines (does that ring a bell?). Technicians would try to guess what was wrong by the noise the machines made. The tool of choice? A simple screwdriver (!!). By pressing it against the equipment and feeling its vibration, they would attempt to interpret the problem. After the diagnostic, the conclusion was scribbled on a piece of paper: “Come back in three months to see if this machine is working well.” Everything was as manual as it could be. Even in an age of computers and smartphones, many industrial facilities still operate with outdated systems. Maintenance engineers may no longer press a screwdriver to a motor to “listen” for problems, but they often rely on the same guesswork. Most still depend on sharpened ears to catch unusual noises, or on rigid, calendar-based maintenance schedules that fail to capture what is really happening inside the machines.

When machines stop, everything stops (including revenue)

Ingredion is one of the world's leading providers of plant-based ingredients. With a market cap of USD ~8bn, factories in more than 20 countries, and customers in over 100, the scale is massive. Yet even at this level, a single failure can be devastating. At its North Kansas City plant, a critical pump failure forced a full three-day shutdown. In Brazil, at the Mogi Guaçu facility, Tractian’s solution helped Ingredion avoid over 700 hours of downtime. These examples highlight a simple truth: every production pause translates directly into lost revenue and profits, while piling stress on maintenance teams who sacrifice sleep and family time to get operations back online. According to a study made by Aberdeen Research, unplanned downtime in manufacturing can cost a company as much as USD 260k/hour. And these are not small or outdated factories. They belong to some of the world’s most modern, global multinationals, which proves that downtime is a universal, costly pain point across industries. According to Siemens, the world’s 500 largest companies lose 11% of their revenue because of machine downtime, equivalent to USD 1.4 trillion annually, or the GDP of a major industrial nation like Spain. A downtime problem is a revenue problem.

Fixing machines after they fail is still the norm

Now you’ve heard Leo’s brother’s story about leaving Christmas dinner, and Igor’s story about his father walking out of birthdays to head back to the factory. These are just two among thousands of stories maintenance workers could tell. The root cause is simple: most of the industry still works by fixing machines only after they fail. This means higher repair costs, unexpected production losses, and more sleepless nights (and white hair) for maintenance teams. Industry data confirms the scope of the problem. Companies spend, on average, 80% of their technicians’ time on reactive maintenance and as much as 40% of their budgets on poorly managed programs. In 2017, Deloitte estimated that inefficient maintenance costs U.S. manufacturers USD 50 billion per year and reduces production capacity by 5% to 20%.

Misaligned incentives in industrial maintenance

Another factor that prevents factories from optimizing maintenance is that machine manufacturers often profit from scheduled services. As Charlie Munger said, “Show me the incentives, and I will show the outcomes”. The incentives of the manufacturers are not always expected to maximize maintenance. Because competition in equipment sales is intense, margins on the machines themselves are usually tight. To compensate, many producers rely on value-added services like maintenance to drive profitability. This creates a misaligned incentive: manufacturers encourage frequent and sometimes unnecessary maintenance, not because the machines require it, but because it sustains their revenue model.

Opportunity: Serving the Silent Hero

Tractian decided to focus on solving the problem of a persona. When startups look for problems to solve, the question is usually “which one?” For Tractian, the question was always “who?.” The visceral, strong connection the founders had to the problem made them really care about the persona they were servicing. This pain has a face: the maintenance engineer — the person whose phone rings in the middle of the night when a machine fails, who shoulders the blame when production halts, and who quietly keeps factories running. The three founders understood this persona intimately through their own family ties to the industry. For them, it was never about chasing market size or abstract opportunities. It was about solving the real, day-to-day struggles of the silent heroes who keep the industrial world alive.

As mentioned earlier, factories, and the maintenance workers who keep them alive, are everywhere. When Igor, Gabriel, and Leo realized the scale of the opportunity, they had their “aha moment”: Tractian could become the go-to tool for maintenance engineers worldwide. Igor recalls it clearly:

“I remember opening the Siemens’ website and seeing that they operate in more than 180 countries. So, if we serve industrial clients, we could potentially be in every country of the world”.

The first step after that realization was to lock down every online domain they could: tractian.com, tractian.com.br, tractian.com.mx, and 37 more. The mission was clear from day one: build a company designed to serve maintenance technicians across the globe.

Product: Cracking the Real Pain

Tractian offers a hardware–software platform that combines state-of-the-art sensors, advanced AI, real-time data, and management tools to give maintenance teams the ability to monitor, predict, and act on machinery performance in real time. The ambition is clear: to become the ultimate industrial co-pilot. Big, fancy words above, huh? But let’s take a deeper dive into how Tractian’s product became what it is today. Tractian’s first product thesis was to build a machine-behavior prediction software that could run on top of the hardware factories already had. Makes sense in theory, right? It’s an asset-light solution leaned into the founders’ strength, software. But in practice, it didn’t solve the real pain of maintenance workers. The abyss was deeper. Most of Tractian’s potential clients didn't even have the baseline data the product needed. Integrations were slow and heavily dependent on IT teams whose priorities rarely aligned with maintenance urgency. The result? A go-to-market strategy that risked stalling before it even began. For an early-stage startup still searching for product-market fit, with very limited resources, these hurdles became existential. As Igor recalls:

“In the first 12 months, we wanted to fool ourselves that it was possible to only have a software solution”.

Alan Kay, the famous American computer scientist, once said (and was later quoted by Steve Jobs):

“If you are serious about your software, you should make your own hardware”.

Tractian’s new chapter begins here. After talking to more than 80 industrial players worldwide, Igor, Gabriel, and Leo realized they would need to build their own hardware if they wanted to truly solve the problem at hand. They decided to do the “dirty work” themselves. For the first sensor prototype, they sourced all components themselves, and spent long nights and Leo and Gabriel’s apartment garage assembling it by hand.

This episode highlights one of the founders’ defining traits: their strong conviction in their own ideas. Once they iterate, analyze, and make a decision, they commit to it — even if it’s unpopular. They remain open to new evidence, but they start from a place of independent judgment rather than consensus. At the time, many VC funds passed on Tractian precisely because of the hardware component. Back to the product: the first version was nicknamed the “band-aid.” The name, slightly cheesy, captured how it worked. The sensor could provide an early health check on a machine, predicting whether something was about to go wrong. Even in its earliest form, the product proved there was demand. Tractian managed to land demos and quickly closed contracts with major industrial players such as Yara, Embraer, Ambev, and ArcelorMittal. If companies of this scale were willing to test a young startup’s solution, it was clear the value proposition was real. While Tractian was gaining initial traction with clients, it secured a spot at YCombinator and received Norte’s first check. A few months later, the company closed its seed round, led by DGF and followed by YCombinator, Norte, Soma Capital and notable angels such as Claudia Massei (Siemens) and Parker Treacy (Cobli). Not long after, the founders swapped the “band-aid” label for a more memorable one: the “Shazam of the machines”. The phrase, suggested during their time at YCombinator, drew on the popular app that uses AI to identify songs. In the same way, Tractian applies artificial intelligence to interpret the sounds and vibrations of machines, spotting potential failures before they happen. Emphasis for the explicit use of the term artificial intelligence. Remember this was early 2021, well before “AI” became the buzzword it is today.

Scaling the Product: the Tractian Way

With a validated product and early clients on board, it was time to scale. But how could a hardware startup in such a traditional industry grow quickly without a big marketing budget The answer came from the founders’ unique style: an obsessive focus on understanding their users, a willingness to get their hands dirty, and the conviction to stick to their own path. On weekends, Igor, Gabriel, and Leo spent entire days immersing themselves in the world of maintenance workers. As Leo explains:

“This is about having an obsessive focus on truly understanding the persona, and not outsourcing that process. We were fascinated by it, we’d spend hours on YouTube watching the maintenance community”.

One of those YouTube marathons led to a key discovery:

“We saw a livestream on YouTube with over a thousand people tuned in, speaking their own dialect, calling a motor a ‘vibrating pig’”.

Don’t ask us why these maintenance workers called a motor a “vibrating pig”, but focus on the powerful finding: there was a massive, underserved community of maintenance professionals hungry for technical content, exchanging knowledge, and speaking in a language only insiders understood. Tractian found a tribe. They took a bold bet. Out of that discovery came one of the most innovative go-to-market strategies: community-based selling. Instead of competing for attention in crowded, traditional channels, Tractian chose to nurture and empower the industry’s own organic communities. Igor explained this approach in a 2022 interview with Lucas Abreu:

“From very early on, we decided to adopt a community-based selling strategy, which involves engaging with organic media and communities, feeding them with quality content, and fostering interaction among personas eager for relevant, niche-specific knowledge. With this approach, we built authority and trust in the sector by acquiring communication outlets, keeping their independence intact, while influencing the new path forward.”

The execution was methodical. Tractian acquired a stake in Revista da Manutenção, Brazil’s leading maintenance content platform, became partners of Predyc, a Mexican education platform, and launched their own U.S podcast, The Maintainers. (All of these cases were mentioned at Sunday Drops in 2022).

Again, mentioning Charlie Munger. He used to say: “In business, the best strategy is often to double down on a winning one”. That’s exactly what Tractian did. The community-first strategy created a global flywheel: technicians and engineers see the company as an ally and educator, not just a vendor. To this day, inbound leads remain the foundation of how Tractian captures attention and drives new sales.

You don’t buy from salesmen, you buy from engineers

Another distinctive aspect of Tractian’s sales strategy is who does the selling. Instead of hiring traditional salespeople, they put engineers, often former maintenance managers, at the front line. For Tractian, credibility is everything. Factory workers, like Igor’s father or Leo’s brother, want to talk to people who have been in their shoes. These engineers speak the language of the maintenance floor, know the frustrations firsthand, they know what a “vibrating pig” is. That shared experience builds trust quickly and turns conversations into authentic exchanges rather than scripted sales pitches, one of the reasons Tractian earns buy-in so quickly.

Expanding inside its client base

Tractian usually enters through the person who feels the pain: the maintenance engineer. They built a product designed to integrate as quickly as possible and, over time, expands within the customer base. Once Tractian enters a client through a plant manager or maintenance worker, it quickly earns the attention of economic decision makers by proving ROI on the shop floor. From there, it builds case studies at the plant level that pave the way for corporate-level adoption, prompting companies to expand Tractian’s solution into new factories. Ingredion, the global ingredient company that we mentioned before, is again a good example. Tractian’s first contract was at the Mogi Guaçu, Brazil, plant, where it prevented more than 200 mechanical failures in the first phase. As one reliability supervisor explained:

“Since our factory is massive (over 1.5km long with thousands of machines), we often have to drive between equipment, spending hours just to run one inspection. By the time we made the reading, returned and analyzed the data, the machine had already broken down.”

The success in Brazil became a case study for global expansion. Soon, Tractian was implemented at Ingredion’s flagship Indianapolis plant in the U.S., considered one of the company’s most innovative facilities, as well as its factory in Cali, Colombia. Today, the partnership spans 10 factories across 4 countries, growing 17x from the initial pilot — proof of how Tractian expands from one plant to a global footprint. Tractian has a net revenue retention rate above 190%. This means that even if all sales efforts stopped today, the company would still grow more than 90% year over year from its existing customer base. This expansion comes from two main levers:

Expanding with existing plants, as described above.
Introducing new products, which multiplies the value delivered per client.

New products: becoming the industrial co-pilot

Just as the company was growing at a rapid pace, the founders decided to add complexity and launch new products. The rationale was to generate more value for the end customer and address additional pain points to maximize machine uptime. This evolution was driven by the goal of solving multiple problems for the same economic decision-maker. Igor explains with a sharp analogy:

“This industry is like selling a mattress. If you’re the manufacturer, you can’t just sell the pillow top, the pillow, or the pillowcase — the core pain remains with the person sleeping on the mattress. In our case, we saw the same dynamic in industries: the pain is the same, and there’s potential to offer relevant solutions to that very person.”

The strategy is maximum centralization around the economic buyer, who is the single point of contact managing multiple budgets and facing multiple related pain points. As Jeff Bezos says: expanding the product line only makes sense if you generate more value for the end customer without diluting your own. With that in mind, Tractian has built a suite of five integrated solutions that extend its reach across the factory floor:

Smart Trac: A third-generation sensor that monitors vibration, temperature, runtime, and RPM data in real time. Its AI thresholds cut down on false alarms, while supervised learning identifies root causes with contextual diagnosis and feedback.
TracOS: A reliability and management platform that organizes every asset in a plant, helping operators streamline maintenance and optimize performance.
Energy Trac: A monitoring system that tracks energy consumption across equipment, diagnosing inefficiencies, preventing failures, and cutting unnecessary costs.
Omni Trac: A connectivity layer hardware that bridges fragmented legacy systems with the cloud, unlocking siloed data and applying dedicated AI models for deeper insights.
Uni Trac: Think of it as a “Chromecast for machines”: a sensor that connects older, analog devices to the cloud, enabling real-time monitoring of key variables.

The ultimate ambition is clear: to become the industrial copilot of every factory in the world. The flywheel driving this vision is strong. Tractian’s hardware acts as the entry point, enabling adoption on the plant floor. From there, every sensor feeds into a vast proprietary dataset: real-world machine performance, operating conditions, OEM manuals, maintenance records, and failure analyses. This unique dataset positions Tractian as the system of record for the industry, building not only operational visibility but also a proprietary intelligence layer. Over time, this intelligence evolves into assisted operations: a trusted co-pilot that guides decisions across the plant. It’s a moat that is both data-rich and difficult to replicate.

Global mode, from day zero

Tractian was born global. From the start, the founders secured domains in 30+ countries, signaling their intent to play on an international stage. The company is headquartered in Atlanta, Georgia, USA. But being global is not the same as expanding. For Tractian, each new market meant rolling up their sleeves. Whenever a new country opened, one of the founders moved there personally. When the company launched in Mexico, Leo relocated, immersed himself in the culture, and closed the first clients himself.

The vision behind this approach is universal. “Whether they speak English, Spanish, or Portuguese, the problem is the same,” Igor explains. Machines break the same way in São Paulo, Mexico City, or Atlanta. And everywhere, there’s a maintenance engineer — the invisible hero — who gets the late-night call to fix them. The strategy mix set Tractian on a steep growth curve. Since 1Q21, the company has sustained 40.8% quarterly compound growth, as reflected in the ARR Graph below.

ARR Growth (indexed 2Q21 = 100)

AI at the Core of Tractian

Tractian has always been an AI company. Since its foundation (and the first deck is there to prove it), Igor, Gabriel, and Leo understood that the heart of the solution lay in predicting machine behavior from both structured and unstructured data generated by industrial equipment. Over time, as machine learning and AI capabilities matured, the product evolved through three distinct generations:

Generation 1 - Descriptive Analysis: The system detected anomalies and triggered basic alerts whenever machines deviated from normal behavior. At this stage, human involvement was total: technicians had to interpret each signal and decide what to do.
Generation 2 - Predictive Diagnostics: AI models began spotting patterns and anticipating problems before they became critical. Instead of flooding users with alerts, the system only flagged issues when there was a high probability of failure. AI shifted from being a passive observer to an active assistant in decision-making.
Generation 3 - Prescriptive Automations: Tractian went beyond simply predicting failures. The system now explains underlying causes and recommends specific corrective actions. Decision-making is increasingly automated: from pinpointing which component is likely to fail, to suggesting what maintenance steps to take.

This progression in capabilities directly reflects the evolution of Tractian’s most valuable asset: data. The higher the quality of data, the more accurate the algorithms, and the more powerful the solution. Today, Tractian has accumulated over 3 billion indexed files, 20 million asset models, 500,000 components, and 300,000 datasheets. Capturing and structuring this data is no trivial task. It’s a challenge that doubles as one of Tractian’s strongest entry barriers. Unlike synthetic datasets, real-world industrial data must be meticulously labeled, validated, and tested under conditions that are often unpredictable. This mirrors the hurdles faced by other companies operating in complex physical environments. Tesla, for example, cannot rely solely on simulations to train its autonomous driving systems — it needs billions of real kilometers driven, with vehicles exposed to all the unpredictability of actual roads. Similarly, Tractian’s intelligence relies on massive amounts of data collected directly from industrial machines, operating across different environments, temperatures, humidity levels, and load conditions. On top of that, Tractian now augments this proprietary base with data generated in its own intelligence center, further reinforcing the flywheel: more machines connected → more real-world data collected → smarter algorithms → more value for customers → even more machines connected.

The result is a model fundamentally different from generalist solutions: one designed to deliver real-world outcomes in complex industrial environments. Every new client doesn’t just benefit individually; they make the whole system smarter. This creates a unique network effect: when one plant solves a vibration anomaly on a specific type of pump, the insight automatically propagates to similar machines across all other connected factories. The impact is both measurable and direct. Tractian reduces downtime, prevents catastrophic failures, and generates tangible ROI. And in the industrial world, precision is non-negotiable: a single wrong prediction can cost millions in unplanned shutdowns. This evolutionary pressure has shaped Tractian’s AI into systems that are more reliable, specialized, and trustworthy than any generalist application. To quantify this, Tractian commissioned a study with AtlasIntel covering 200 industrial companies. The results speak for themselves: 43% decrease in unplanned downtime, 11p.p increase in machine availability, and a 38% boost in productivity. The equation is simple… and powerful: more machine uptime means more revenue. Tractian sits at a rare sweet spot: mature enough to have built a robust data foundation, yet young enough to move fast and create category-defining products. The company has benefited from a perfect convergence. On one side, IoT sensors finally became affordable and reliable at scale. On the other hand, the market continued to underestimate the potential of specialized industrial AI. Tractian was uniquely positioned to ride this wave, combining the physical footprint of connected sensors with the intelligence layer that turns raw data into actionable insights.

This timing coincided with a structural shift in the industry. For decades, equipment manufacturers (OEMs) controlled both the sale and the maintenance of industrial machines. The model carried an obvious conflict of interest: profit came from frequent breakdowns, not from equipment longevity. The arrival of GenAI is breaking this dynamic. Tasks once locked inside OEM service contracts — diagnosing failures, prescribing fixes, optimizing schedules — can now be performed independently through intelligent systems. Maintenance no longer needs to follow rigid timelines designed to serve suppliers rather than operators. Tractian positioned itself as the bridge for this transition: an independent layer of intelligence that works exclusively for the machine operator, not the OEM. The company captured the sweet spot of industrial AI, where urgent market pain meets specialized technical capability. The result is a compounding advantage: every sensor installed strengthens the moat, every failure detected sharpens the algorithm, and every client acquired makes the product smarter for all. At the core of this strategy is Tractian’s ambition to unify the industrial system of record, turning scattered machine data into a single source of truth, and then layering intelligence on top to drive autonomous decision-making.

Actionable Insights from this Story

Focus on the "Who," Not the "What"

Tractian started with a person they wanted to help: the maintenance engineer. The lesson: instead of asking "What should we build?" ask "Whose life do we want to change?" The clearer your mental picture of that person, the easier every other decision becomes.

Problem Conviction Over Solution Flexibility

Be stubborn about the problem, flexible about the solution. Tractian never wavered on preventing machine downtime but completely reimagined their approach when software-only hit roadblocks. They headed to Santa Ifigênia with screwdrivers and circuit boards, willing to do whatever it took.

You can only pivot gracefully when you're anchored by something deeper than your original product hypothesis.

Create Your Own Playbook Through First Principles

Instead of following B2B best practices, Tractian discovered maintenance professionals on YouTube calling motors "vibrating pigs" and built their entire go-to-market around that community. They spent weekends watching their customers, not just reading reports about them.

Building your own playbook means resisting the comfort of proven frameworks and getting obsessively close to your users.

The Power of Founder-Market Fit

The family connection with the pain gave the founders intuitive insights that couldn't be replicated through research. Founder-market fit creates advantages that competitors can't copy because it becomes part of company culture at the deepest level.

Global Vision with Hyper-Local Execution

Tractian secured domains in 40+ countries from day one but expanded intensely personally like Leo moved to Mexico himself rather than hiring a country manager. They could see universal patterns (machines fail everywhere the same way) while respecting local nuances.

Think big, act small. Scale the vision, never scale away from direct customer contact.

Build Moats Through Network Effects

Tractian's deepest advantage is the data flywheel where every new client makes the system smarter for everyone. This creates compounding value that becomes impossible to compete with over time.

The most defensible businesses create value that compounds across their customer base, making each new client a strategic asset for all existing ones.

The Discipline of Saying No

Tractian could have expanded into countless adjacent opportunities but doubled down on machine uptime. This focus created compound advantages: deeper expertise, stronger relationships, clearer positioning.

The maintenance engineer whose phone rings at 3 AM remains at the center of everything they build. That clarity of purpose may be their most replicable lesson.

Published by José Pedro Cacheado and Lucas Abreu.