Question 1

How does engagement work?

Accepted Answer

The model is assessed according to the project. First we understand the problem and map the complexity; from there we define scope, deliverables and deadlines, and only then do we discuss the engagement format — which can be a defined project or a technology partnership, when the idea is promising enough for us to share the risk. To size anything we need to know what goes in and out of the process you want to automate, and that is what the free fifteen-minute call is for.

Question 2

How fast do you ship?

Accepted Answer

We work in weeks, not quarters. The first working deliverable usually ships within the first two weeks, because we use mature tools — n8n, LangChain, Next.js — instead of rebuilding everything from scratch. Larger projects are sliced into short, verifiable deliveries so you see something running well before the full scope is done.

Question 3

Do you use n8n or LangChain? Which one is better?

Accepted Answer

Both, and the choice depends on the problem. n8n is better when the challenge is integrating systems and orchestrating a flow with predictable steps — every node is visual and auditable. LangChain comes in when language reasoning is required: agents that decide which tool to call, RAG systems answering from a knowledge base, chatbots wired into business rules. In practice most of our production systems combine the two.

Question 4

Do I own the code and the infrastructure?

Accepted Answer

Yes. Code, infrastructure and credentials are yours from start to finish. We hand over with documentation and a proper handoff, so your team can operate and evolve the system without depending on us. We don't build vendor lock-in.

Question 5

Will the AI make decisions on its own in my process?

Accepted Answer

Only if you want it to — and usually we advise against it. Our default pattern is that the model reads, extracts and converses, while business decisions stay in explicit, versioned, testable rules. In the credit pre-analysis engine we built, for instance, AI reads documents and images, but no credit conclusion is generated by a model. A system that decides on its own without leaving a trace does not reach production.

Question 6

Do you work with clients outside Brazil?

Accepted Answer

Yes. We are based in Goiás, Brazil, and work remotely with clients across Brazil and abroad, in Portuguese and English. The whole process — discovery, delivery, review and handoff — runs remotely, and that is how we already run the systems we keep in production today.

Question 7

How does the free 15-minute consultation work?

Accepted Answer

You describe the process you want to automate and you leave with a technical path: which tools to use, in what order, what is straightforward and where the risk sits. It is not a sales meeting: we don't present a commercial proposal in that call. If it makes sense to work together afterwards, then we talk about scope.

Credit pre-analysis: from a full business day to minutes

The challenge

A credit decision cannot come from a model

Bureau queries cost money

A failing source cannot halt everything

How we solved it

Four independent stages

AI only at the reading stage

A failing collector becomes a gap, not an error

The report is assembled from a template

The outcome

What this architecture teaches

Stack

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