AI agents
Business-process automation with agents trained on your own documents and rules — always with a human in the loop.
Outcome: repetitive work leaves your team’s queue.
Agentic AI · IoT · Data
AI agents trained on your context take over repetitive back-office work — with a human in the loop, real governance, and results measured against your baseline.
The problem
Every company has routines that eat hours and require no judgment. They tie up the team, cost real money, and grow quietly.
Answering the same questions, copying data between systems, building the same report every Monday. Work no one should be doing by hand.
Promising proofs of concept that never reach production — because they lacked a process, an owner, and a clear metric to measure against.
The pressure to do more with less is real. But automating without governance, traceability, and LGPD compliance just trades one problem for another.
What we do
Three connected fronts: the agents that execute, the teams that run them, and the data that feeds them.
Business-process automation with agents trained on your own documents and rules — always with a human in the loop.
Outcome: repetitive work leaves your team’s queue.
We equip your business teams to build and maintain their own automations, with method and best practices.
Outcome: internal autonomy, less vendor dependency.
The data foundation that feeds the agents: source integration, analytics, and plug-and-play sensors when data comes from the physical world.
Outcome: decisions and agents driven by trustworthy data.
How we work
We don’t sell AI by the pound. We pick one process, prove the value at small scale, and only then scale up.
We dig into the real routine: where the time goes, what rules exist, what gets stuck. Without this, no automation holds up.
One carefully chosen process, one measurable pilot, no monumental project. Fast to stand up, safe to test.
We compare with how it’s done today: time, cost, quality. If the gain shows up, we move on. If not, we adjust or stop.
What works goes to production — with a human owner per automation, traceability, and LGPD compliance.
↻ It’s a cycle: every process that runs generates data and ideas for the next one.
Why baldo.io
We act as a wise guide who demystifies the complex world of technology so you can focus on what you do best.
Human in the loop, a human owner per automation, and LGPD compliance. Transparency about what the agent does and why.
Continuity, not a one-off project. Solutions that evolve through continuous improvement alongside your business.
We explain every choice in plain language. You understand what’s being built and decide with clarity.
Data sovereignty
For regulated processes or back-office data, the AI’s architecture matters as much as the outcome. Open-weight models, your own infrastructure, and a closed perimeter change the risk calculus.
Open-weight models run on-premise or in a private/Brazilian cloud, instead of sending sensitive data to a closed foreign SaaS API.
Outcome: the model runs where you decide, not where the vendor decides.
Agents operate inside your own infrastructure or VPC — you define exactly which data, if any, crosses that boundary.
Outcome: full control over what leaves the environment.
Data residency, traceability, and LGPD alignment become verifiable inside your own infrastructure — not a clause in a third-party contract.
Outcome: governance you audit, not governance you take on faith.
An open model running on your own infrastructure doesn’t depend on a foreign vendor’s export policy or commercial availability. If an export-control rule or a corporate decision cuts off access to an API, your operation keeps running.
Outcome: continuity that isn’t hostage to a border or a vendor.
Let’s talk
Tell us in one sentence what eats up your team’s time the most. We’ll reply with a concrete path — no strings attached.
Prefer email?
[email protected]