Service 03
AI agents & copilots
Colombia
Automatizaciones Digitales

Assistants that actually answer.

Assistants that read your data and answer with evidence — citing where each claim came from, with a human approving before anything ships.

[ What it solves ]

The problem,
not the tool

01

The generic chat doesn’t know your company

A general-purpose model answers everything well and your business poorly. The difference is giving it access to your documents, your databases and your rules.

02

Nobody signs what they can’t verify

An answer without a source can’t be used to decide. Our agents cite the document and the exact fragment each claim came from.

03

The fear of it acting alone

An agent that writes emails or moves data unsupervised is a risk. We put human approval at the point where the action leaves for the world.

[ How we do it ]

The method,
made concrete

01

We scope what it can touch

Before the first prompt we decide which sources it reads and which actions it’s allowed. An agent without limits is an incident waiting for a date.

02

Retrieval with the source in sight

The agent searches your documents and answers with the citation. If it finds no backing, it says so instead of making things up.

03

A human at the exit point

Generating is cheap; publishing or sending is what has consequences. That’s where the approval goes — not earlier.

04

We measure how well it answers

A set of questions with known answers, evaluated on every change. Without that, "I improved the prompt" is an opinion.

What we use

Claude APIClaude Agent SDKMCPRAGLLM evalsCopilot StudioMicrosoft 365 Agentsn8nWhatsApp Business API
[ In the work ]

Where you see it
running

Real projects from this service.

[ Frequently asked ]

What we get
asked

What exactly is an AI agent?

An assistant that reads your data — documents, databases, email — and answers or acts with evidence. Unlike a chat, it has access to concrete sources, tools to query them, and explicit limits on what it can do without permission.

Are my documents exposed to the model?

It depends on the architecture, and it’s a decision made at the start. You can work with providers that don’t train on your data, or keep everything inside your own infrastructure. We define it before connecting the first source.

What if the agent gets it wrong?

That’s why we cite the source and put human approval where the action ships. An agent that errs while showing where its answer came from is correctable; one that answers confidently without backing is not.

[ The other services ]

We also
do

[ Got something that should be running on its own? ]

Let’s talk.

hablemos@digiautom.com

Reply within 24 hours · Colombia

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