Twenty years of data,
within the member's reach

A layer of access, interpretation, and communication on top of technical information the client already had in digital form.

Client COLAVECOAgro-industrial laboratory · Cooperative
Industry AgribusinessTechnical analysis laboratory
Year 2026Phase I · Launched in May
Role Product, design, and developmentFrom discovery to adoption
Interactive Digital Annex · main screen
I / Context 01 / 06
The client

A laboratory
with an archive.

COLAVECO is an accredited agro-industrial laboratory located in the Department of Colonia, Uruguay. Among its services to the dairy sector, it offers an individual analysis of each animal in the herd: one sample per cow, with technical results on milk quality and the animal's health status.

The project builds on a little-known trait of the client: for two decades, the results of every analysis have been kept in digital form, systematically. Valuable, organized, available information — that wasn't being put to use by the very people who generated it.

Starting point

Twenty years of technical information, accumulated and carefully preserved. Yet the people generating it couldn't easily consult it or read it in perspective.

II / Challenge 02 / 06
The problem

The information was there.
Reading it wasn't easy.

Farmers received each milk test as an accredited PDF document, technically impeccable. At the end of the document, a static section summarized the information in simple charts: quality traffic lights and lists of the animals that needed attention. It did the job, but it was frozen in time.

Comparing one month's test with one from six months earlier meant opening two documents. Following the history of a specific animal meant going through each one by hand. Sharing the list of problem animals with a technical advisor meant transcribing it manually. The friction wasn't in the data. It was in how it had to be read.

How do we turn twenty years of archived data into real value for the member — without charging more, without breaking what already works?

And beneath that question, a more strategic one: how to help COLAVECO evolve from an analysis provider into a technical partner to its farmers.

III / Approach 03 / 06
The hypothesis

From the PDF that arrives
to the channel that awaits.

The PDF arrives and gets filed away. The application, by contrast, is a permanent access channel where the information stays alive, comparable, and exportable.

We decided not to reinvent the interpretation the laboratory was already doing. We knew it, the members knew it, it worked. What we did was give it a new space to breathe — and add what a static PDF could never do.

  1. 01

    Build on what already worked.

    Farmers were already familiar with a certain vocabulary and certain visual codes — color categories, thresholds, technical terminology. The application extends that existing language instead of replacing it, flattening the adoption curve.

  2. 02

    Start with accessibility, not intelligence.

    Before adding sophisticated analysis, solve the basics: let farmers consult their entire history on a single screen, compare results across periods, and export the information to share it with whoever needs it.

  3. 03

    Design for different levels of use.

    The same application serves those looking for a quick summary of the herd's status and those who need to explore the information in greater detail. The initial screens show the essentials; filtering and export tools remain available for whoever requires them.

IV / What we built 04 / 06

Six capabilities,
a single experience.

The Phase I capabilities of the Interactive Digital Annex (Anexo Digital Interactivo, its name in Spanish), in the order members find them when they sign in.

5.1 · Access

Farmers sign in and see only what's theirs.

Login linked to the member's account. Each farmer finds their own history; nothing more, nothing less. Credentials are handed over at the start of the project and can be delegated to trusted technicians.

Interactive Digital Annex login screen
5.2 · History

Every milk test, in one place.

What used to be loose documents in a folder is now a searchable screen: date, type of analysis, number of samples, and a summary indicator for each test. The full historical archive processed by the laboratory becomes available with no intermediate steps.

List of milk test reports
5.3 · Selected test

The interpretation that already existed, now explorable.

The test's main indicators — overall distribution of the herd, cases requiring attention, and evolution since the previous test — are linked to the concrete list of animals behind each category. Anyone who needs to act on a group can view it and export it in one step.

Detail view of a milk test report
5.4 · Historical comparison

Twelve tests at a single glance.

A stacked visualization shows the herd's evolution across previous tests. Farmers choose the comparison window — the last 3, 6, or 12 analyses — and the most recent test always sits on the right as the reference.

Historical comparison of milk tests
5.5 · Impact estimate

A first indicator of the associated cost.

Based on the test results and a bibliographic reference recognized in the sector, the application delivers a first estimate of the productive impact associated with the herd's health status. The indicator is labeled as preliminary; later iterations will incorporate per-animal data to refine it.

Productive impact estimate
5.6 · Exploration

For those who need to go deeper.

A complete table with every sample in the test and every parameter analyzed, filterable by any criterion: identifier, out-of-range values, specific parameters. Designed for the technically minded farmer or their advisor, it complements the summary views without imposing its complexity on anyone looking for a quick read.

Filterable results table
V / Phase I outcomes 05 / 06

What Phase I
delivers.

Three dimensions where the tool produces an immediate change on information the cooperative already had.

+20 Years of information available

The complete history enters the tool from day one, with no migrations and no setbacks.

×12 Friction reduction

Comparing the evolution across twelve periods went from opening twelve separate documents to a single screen.

0 Additional cost

The tool sits on top of the analyses the client already pays for, with no additional services for the user.

VI / What's next 06 / 06
Roadmap

This is
a first step.

Phase I covers the core functionality members need to access, interpret, and share the information from their milk tests. The next iterations, identified during discovery, deepen the interpretation and expand the decisions farmers can make from the data.

  1. 01

    Incorporate per-animal data.

    So the impact estimate stops being preliminary and becomes a calculation backed by the actual production of each animal in the herd.

  2. 02

    Herd optimization.

    Identify which animals, if removed from the herd, improve the overall quality of the product enough to justify a better market price. A concrete decision, with a calculation behind it.

  3. 03

    More interpretation, less effort.

    Early alerts, automatic suggestions, and comparison against anonymous cohorts. Features that assist farmers without requiring their active involvement.

Each iteration builds on the previous one. Phase I lays the foundation the next ones will be built on.

Unused data?

Let's talk about the next step.

For organizations with accumulated information that hasn't yet been turned into value for their users. Every project starts with a short discovery engagement to define scope and priorities, no strings attached.

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