Data engineering
that ships to production

We take off your hands the report someone rebuilds every week, the number nobody trusts and the process that stalls waiting for a person. Closed scope, firm deadline, price agreed upfront.

The cost of living with bad data

“Poor data quality costs organizations at least $12.9 million a year on average.”

Gartner, 2020 research · gartner.com

$12.9M per year, on average

What poor data quality costs an organization, at least, according to Gartner (2020). The qualifier is Gartner's own.

59% do not measure

Of organizations do not measure the quality of their own data (Gartner). Without measuring, there is no way to know what the problem costs.

39% of time on preparation

The share of time data professionals spend preparing and cleaning data, more than training, selecting and deploying models combined (Anaconda, 2021).

An honest caveat: the Gartner research is from 2020 and its methodology is not public. We treat it as an order of magnitude, not as precision.

Six services, end to end

🔁

Automated reporting

The report someone rebuilds by hand every week gets assembled, checked and delivered on the schedule you set.

📡

Market monitoring

Competitor pricing and portal data collected automatically, with alerts when something changes and history to compare.

🔎

Data diagnostics

When reports disagree, we trace the origin of every field and define a single source of truth.

Dedicated sprint

One business day of engineering with closed scope and a firm deadline, for when something broke and is already costing money.

🤖

AI agents

End-to-end process automation using rules and document analysis, with a human approval gate on anything irreversible.

💬

CRM with AI agents

Lead qualification over WhatsApp with automatic follow-up, synced to your CRM.

Four steps, nothing agreed after the fact

1

Free diagnostic

We map your scenario, stack and pain points. No cost, no commitment.

2

Plan and architecture

We design the solution with scope, timeline and a fixed price, agreed before anything starts.

3

Implementation

We build pipelines, tests and documentation, in your repository.

4

Handover

Code and documentation in your hands. No lock-in.

Frequently asked

What does a data engineering consultancy actually do?

It helps a company collect, organize, transform and serve data reliably, building ETL/ELT pipelines, warehouses and the cloud infrastructure that supports analytics, BI and AI.

Do you work with clients outside Brazil?

Yes. We are based in Curitiba, Brazil, and work remotely. Invoicing in USD is available.

How does an engagement start?

With a free diagnostic: we map the current process, where it breaks and what needs to stop being done by hand. Scope, timeline and price are agreed before any work begins.

What is a Dedicated Sprint?

One business day of engineering with closed scope and a firm deadline, for when something broke and is already costing money.

Start with a free diagnostic