Challenge

A field representative in agribusiness visits dealerships, travels to rural properties, records incidents, and closes deals in locations where cell phone signal is a variable, not a guarantee. Therefore, the app they use needs to work regardless of what the antenna provides.

Tekoa Tecnologia understands this from the inside. It was born within a highly complex agricultural ecosystem, with agricultural production and input industries operating together. This origin shaped Tekoa Eve: a field team management platform built by those who understand what happens outside the office. With over a thousand active users and a presence in every state of Brazil and Paraguay, Eve has already proven its value in the market.

The challenge was that, with rapid growth, Tekoa needed to know what was accumulating beneath the surface, in the code, on the frontend, and on the backend, before the scale amplified what was not yet visible.

Products that gain traction quickly accumulate technical decisions made under delivery pressure. Each sprint adds layers. The original architecture solves today's problems, but it wasn't always designed for tomorrow's volume. And when the product operates in the field, with local caching and offline synchronization, the margin for unnoticed problems is even greater.

Tekoa approached Evo Systems seeking precisely that: an external, structured, and documented technical assessment. Not to fix something that was already broken, but to map out what needed fixing before growth made repairs more expensive.

Transformation_

The project scope was designed in three complementary layers.

The first was mapping the screens of Tekoa Eve. The app's 175 screens were documented by name and visual capture, creating a complete inventory of what exists in the interface. This work seems simple, but it is rarely done systematically in products that evolve in sprints: documentation rarely keeps pace with the development rhythm.

The second layer was the technical analysis. The code was evaluated for non-conformities in the frontend and backend, with special attention to the offline architecture and the efficiency of data persistence in caching. In an app for field representatives, the offline layer is not an implementation detail. It is a condition for the product to function in the real-world environment. In the frontend, the diagnosis identified 11 problems. In the backend, additional non-conformities were documented, and some of the findings remain under a confidentiality agreement with the client.

The third deliverable was a consolidated screen of problems and suggestions. Each identified nonconformity was recorded, contextualized, and linked to the corresponding screen, forming a reference document that connects the technical diagnosis to the user interface.

The result was a comprehensive technical report: a diagnosis of non-conformities by layer, optimization recommendations, and a standardized presentation structure that became the reference for Tekoa's internal technical communication.

Benefits_

The report fully met the client's expectations. The identified non-conformities were prioritized and incorporated into the development backlog, transforming from unknown problems into roadmap items with documented context, justification, and impact.

This is the practical result of a well-done diagnosis: it's not about fixing the problems, but about being able to fix them in the right order. Without a structured mapping, development teams prioritize what appears first, whether it's a bug reported by the client or a feature requested by sales. With the diagnosis, Tekoa began prioritizing what matters technically, with visibility into what was accumulating and the cost of postponing it.

The standardization of technical documentation was a collateral benefit: the structure developed to present the diagnosis began to be used as a reference for communication with the client and for presenting recommendations in future projects.

There's a specific moment in the life of a digital product when an external technical evaluation yields the greatest return: after traction is proven, but before growth makes each fix more complex and expensive. In the case of Tekoa Eve, this moment was recognized by the team before it became urgent. The product had real users, a nationwide operation, and a demanding usage environment: field, offline, and multiple user profiles. The diagnosis provided visibility into what needed to evolve so that Eve could continue growing with the same consistency that has brought it this far.

Tools used_

• Flutter (Dart)

Your product has traction. Do you know what's accumulating beneath the surface?

This is the perfect time for an external technical assessment: after traction has been proven, before growth makes each correction more complex and expensive. A structured assessment identifies what needs attention while correction is still straightforward.