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Solutions · AI consulting

AI consulting services that end in something running, not in a slide deck

Our AI consulting services start with your operation, not with a model: we map where AI pays off, rank the use cases by impact and feasibility, and stay with your team until the first one is live — in your time zone, in English, Spanish or Portuguese.

How we work
Analyst typing at a desk while two monitors and a laptop show sales charts, retention and margin indicators

Everyone is doing AI. Nobody can say what it returned.

The hard part is no longer the technology — it is choosing. Every vendor has a demo, every team has an idea, and the budget goes to whichever pilot made the most noise that month. Consulting exists to make that call with evidence: what to do first, what to leave for later and what is not worth solving with AI at all.

  • Pilots that demo well and never reach production.
  • AI licenses bought team by team, with nobody measuring the return.
  • Ideas that collapse when someone asks which data they would run on.
  • A different answer to "where do we start" depending on who is in the room.

How we work

From a list of ideas to a plan your team can execute

AI opportunity assessment

We walk through your operation with the people who run it and find where AI actually moves the number.

  • Interviews with the teams doing the work
  • Map of the processes, data and systems involved
  • A shortlist of use cases, not a wish list

Prioritization and roadmap

Every case scored by business impact, effort and risk, so the order stops being a matter of opinion.

  • Impact, effort and risk scored case by case
  • Baseline metric agreed before anything is built
  • The sequence written down, with an owner per case

Build, buy or leave it alone

Some cases are solved by a tool you already pay for. Others need something built around your systems — and we tell you which is which.

  • What you already own reviewed before proposing anything new
  • When it has to be built, our AI agents solution picks it up
  • Vendor dependency and exit cost on the table

AI implementation services

We stay through the rollout: the first case in production, measured against the baseline, with your team learning to run it.

  • Pilot with a success criterion defined up front
  • Production rollout alongside your team
  • Handover: documentation, guidelines and training

Generative AI consulting

Where generative models earn their keep — drafting, classification, extraction, imagery — and where they quietly cost more than they save.

  • Model output compared against your manual process
  • An evaluation set before launch, not after the complaints
  • Limits and failure modes stated in writing

Is your data ready for this?

Most AI projects stall on access and data quality, not on the model. We check that before you commit to anything.

  • Quality, coverage and access reviewed source by source
  • Permissions, privacy and data residency mapped
  • What to fix first and what can wait

Industry cases

What the decision looks like in practice

Ecommerce

Pain

Three teams bought three AI tools. None of them can see the catalog.

Solución

Assessment of the operation → shortlist ranked by margin impact → pricing goes first, with the baseline agreed before anything is built.

One ranked plan, not 20 ideas

B2B services

Pain

Support wants a chatbot. Nobody knows which questions it would actually cover.

Solución

We measure the ticket mix first, define what a good answer looks like, and only then decide what gets built and what stays human.

Success criterion agreed up front

Retail

Pain

A year of AI pilots and no way to tell which one paid off.

Solución

A baseline metric per case, a single roadmap and a scheduled review with the numbers next to each decision.

Every case measured against a baseline

Marketplaces

Pain

Cataloging thousands of products by hand, and a vendor promising AI will fix it.

Solución

We test the model against your own manual process on a real sample, then say whether rolling it out is worth it.

Go / no-go decided on real data

FAQ

What companies ask before hiring AI consulting

What does an AI consulting firm actually deliver?

An honest map and a decision. We review your processes, data and systems with the people who operate them, and hand over a shortlist of use cases ranked by impact and feasibility — each one with the metric it has to move, the data it needs and what it takes to run. That includes the cases we recommend against: knowing what not to automate saves more than one badly chosen pilot. From there you can execute with your own team, with us, or with whoever you prefer.

Do you also build what you recommend, or only advise?

Both, and they are separate decisions. Consulting can stop at the roadmap and still be worth it. When the answer is to build an agent connected to your systems, that work belongs to our AI agents solution; when what you actually need is to see your numbers rather than automate a decision, that is our business intelligence solution and we will say so. What we never do is recommend a project because we happen to be the ones who would build it.

Which AI models do you recommend?

It depends on the case, not on the headlines. Anthropic Claude for complex reasoning and long tasks, OpenAI GPT for generic ones, self-hosted Llama or Mistral when privacy or cost constraints make a commercial API a bad fit. We compare them on your own examples before recommending one, and we design so that swapping the model later does not mean rebuilding everything around it.

Will our data be used to train models?

No. We work with commercial APIs (Anthropic, OpenAI) under terms that exclude your data from training, or with self-hosted models inside your own infrastructure when sensitivity requires it. Which sources a use case is allowed to touch, and who can see the output, is part of the assessment — not an afterthought once something is already running.

We are not a large company. Is AI consulting worth it for us?

Often more than for a large one: a smaller company feels a badly chosen project immediately. It starts with a free 30-minute audit where we look at your operation and tell you honestly whether AI is the answer; within 48 hours you get a written proposal with scope and a fixed cost per phase. And if the honest answer is that your problem is a process problem, you will hear that instead of a proposal.

Ready to boost your business performance?

Let's talk about building it together. No commitment.

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