Work
Agents over warehouses, classification pipelines over years of call history, semantic search that answers rather than lists. A few of the systems we've put into production.
What we do
We work across the whole stack an AI product needs: the model layer, the data underneath, and the product around it, so nothing falls through the gap between vendors.
Plus 7 more, including machine learning, data engineering, mobile, and advisory work. See the full catalogue.
Ways to work together
Every engagement starts with a discovery call, and we quote after it, because a fixed price attached to an unscoped problem helps nobody.
1–2 weeks
Teams with a shortlist of ideas who need an honest read on which are worth building, and what they will actually cost to run.
4–12 weeks
A defined problem that needs to become a working system: a first AI feature, an agent, a retrieval layer, or a model in production.
Monthly, rolling
Ongoing capacity alongside your own engineers, running what we built, extending it, and levelling up the team as we go.
About MOVAX
MOVAX Solutions is a Brazil-based engineering studio. We are deliberately small and deliberately senior, which means the people you meet in the first call are the people who write the code, and nothing gets lost in a handover to a delivery team you never spoke to.
We build applications on top of the best available models rather than training our own, and we build classical machine-learning systems where a model is genuinely the better tool. Both come with the same discipline: evaluation before launch, observability after it, and code you own outright.
That combination of applied AI and the product engineering to put it in front of real users is why clients bring us the projects that stalled somewhere between a demo and a deployment.
Questions
If yours isn't here, ask it directly, and you'll get an answer from an engineer, usually within a day.
A prototype on your real data usually takes two to four weeks, and a production build four to twelve depending on scope. You get a clear timeline after a short discovery call, before any work begins.
We scope each project up front and quote a fixed price for defined work, so there are no surprises. Ongoing work runs as a monthly retainer you can pause or cancel with 30 days' notice.
No. We build applications on top of the leading models (Claude, GPT, Gemini, and strong open-weight options), and we do build classical machine-learning models for prediction and classification. Where a project genuinely needs specialisation, we adapt an existing open model rather than pre-training one.
You do, entirely. Source code, infrastructure, prompts, and cloud accounts are yours from day one and handed over at the end. Nothing is locked to us.
Yes. Most of our work is inside an existing codebase alongside an existing team. We would rather improve what you have than argue for a rewrite, and we only recommend one when the current setup is genuinely blocking you.
Your data is never used to train third-party models, we redact sensitive fields before anything leaves your perimeter, and for regulated workloads we deploy open-weight models entirely inside your own cloud or on-premise.
We assume it will, and design for it: retrieval with citations so claims are checkable, guardrails that block unsafe output, confidence thresholds that escalate to a human, and an evaluation suite that catches regressions before release.
You can take it over, and we hand off with documentation, tests, and dashboards. Or keep us on a support plan for monitoring, improvements, and new features. Both are normal; neither is a trap.
Next step
Tell us what the process looks like today. We'll tell you honestly whether AI is the right tool, what it would take to build, and roughly what it would cost to run.
MOVAX Assistant
Protected by reCAPTCHA. Google's Privacy Policy and Terms of Service apply.
