Before Trampay, I spent several years building payment and income-tracking systems for workers in Brazil's informal economy. Not gig workers specifically, at first. Mostly construction laborers, domestic workers, small street vendors. People whose income arrived in cash, in irregular amounts, with no documentation trail that a financial institution would recognize.
The consistent thing I kept running into was not that these workers were bad with money. Most were managing their finances carefully under genuinely difficult conditions. The problem was that the tools available to them were designed for someone else, and the absence of documentation froze them out of products that would have meaningfully improved their financial position.
The Specific Problem Delivery Workers Face
When the app-based delivery economy in Brazil scaled up in the late 2010s and accelerated through 2020 and 2021, something interesting happened from a financial data perspective. Suddenly there were millions of workers whose income was digital. Every delivery completed, every Pix transfer from the platform, every weekly earnings summary was stored in a digital system. The information existed. It was timestamped, verifiable at source, and organized by delivery platform in ways that cash income never had been.
But almost none of that information was flowing into the credit evaluation system. The platforms were not reporting earnings to credit bureaus. Banks were not connected to platform APIs. A courier who earned R$ 4,000 per month consistently for two years had no formal way to prove that to a lender, because the formal proof systems were built on contracheques and formal payroll records, not app-based earnings history.
Sofia and I talked about this gap a lot in 2024. She had been building predictive income models for financial applications and kept running into the same constraint: the data that mattered most for assessing gig worker creditworthiness was sitting in delivery platform systems, completely disconnected from the financial services infrastructure. The technical gap was not about the complexity of the problem. The signals were there. The connection was not.
What Made Us Think a Product Could Fix This
The Open Finance framework in Brazil gave us confidence that a technical solution was buildable. The Banco Central do Brasil's push toward open banking infrastructure created regulatory and technical precedents for consent-based data sharing between financial systems. A platform that could sit in the middle of that with explicit courier consent, read delivery earnings data, and translate it into verifiable credit-supporting documentation was technically coherent and not obviously going to get shut down by regulatory friction.
The other thing that gave us confidence was the income forecasting piece. Credit invisibility is the structural problem, but it is downstream of a more immediate daily problem: couriers cannot plan their weeks because they have no reliable forecast of what they will earn. A worker with two kids in school, a motorbike loan, and a room rental in Zona Sul is managing a genuinely complex cash flow on information that arrives after the fact. They know what they earned last week. They do not know what they will earn next week.
If we could build an income forecast that was actually useful for planning, rather than a generic average that ignores their specific patterns, we would have something with standalone value. The credit component could grow on top of an income visibility product that people were already using because it helped them in a direct, daily way.
The First Conversations with Couriers
Before we wrote a line of production code, we spent about six weeks talking to couriers in Sao Paulo. In Largo do Piques, near Faria Lima, in Pinheiros, in Santo Andre. We asked about their income: how predictable it felt, what made a good week versus a bad week, what they wished they could plan ahead for.
The conversations were not what we expected. We assumed the main pain point would be credit access. It was a pain point, but the more immediate and universal frustration was unpredictability. Couriers described the stress of not knowing whether a given week would be R$ 800 or R$ 1,600. They described making decisions about household spending on Monday based on last week's earnings, then spending the rest of the week recalibrating when the current week turned out different. Several described the feeling of always running one bad week away from a problem they could not absorb.
That shaped our decision to build the income forecast as the entry point to Trampay, not as a secondary feature. Credit building is the structural fix. Income visibility is the daily utility. Both matter, and the daily utility is what creates the habit of engagement that makes the long-term credit work possible.
What We Are and What We Are Not
Trampay is an income management and credit profile building tool for gig workers. We read your delivery earnings with your consent, forecast your income, and build a credit profile from your verified earnings history that you can use in conversations with our partner lenders.
We are not a bank. We do not hold deposits, we do not lend money, and we do not guarantee that you will receive any particular credit offer. When we say we can help you build a credit profile, we mean we can produce a documented earnings history that lenders in our partner network can evaluate. The credit decision is theirs. What we give you is the ability to walk into that conversation with evidence instead of a blank file.
We are also not trying to be everything. There are a lot of problems in the gig economy financial space. Some of them, like insurance for work-related incidents or equipment financing, are important but are not what we are building right now. Trampay is specifically about income visibility and credit access because those are the two problems we believe we can solve well with a small team and the data connections we have built.
What Early-Access Participants Have Shown Us
We have been running early access in Sao Paulo since late 2025 with a small group of couriers. The patterns have broadly confirmed what the conversations suggested. The income forecast is the feature people use most often, typically checking it on Mondays or Sundays before planning the week. The credit profile feature takes longer to see results, which is expected given that building a documented earnings history takes time.
One thing that has been more pronounced than we expected is the psychological effect of seeing a forecast at all. Multiple participants have described the shift from feeling like they are guessing their way through the week to feeling like they have a framework for decisions. The forecast is not always right. But having it, and understanding how your current week is tracking against it, changes the decision-making process in a way that purely retrospective income data does not.
The credit access piece is early. The couriers who have been in the program longest are starting to have conversations with partner lenders that they could not have had before. That is the outcome we are working toward. It is going to take more time, more couriers, and more lender partners before it is broadly available. But the direction is clear enough that we are confident it is worth building.
We built Trampay because the gap was real and the tools to close it did not exist. Two people with the right background, a technical approach that the regulatory environment supports, and a conviction that 12 million gig workers in Brazil deserve financial tools that reflect how they actually earn. That is the whole story.
