About

About São Tomás

A climate risk company born in the crisis room: rain and flooding, wildfire, asset protection. We build platforms for people who decide with the weather in front of them — and we hold firm opinions about how a number reaches the screen.

Who we are

São Tomás builds and operates climate intelligence platforms for operations whose assets are exposed to the sky. We serve power utilities, transmission operators, telecom, water and sanitation, agriculture, mining, logistics, civil defence, governments, and the financial and insurance market.

Before we were a product company, we were a team that responded to real crises — the Rio Grande do Sul disaster, the 2024 wildfire crisis, operations with civil defence. That is not biography: it is what determines which questions the platforms answer.

We sell projects, not shelf licences. A climate risk platform is only useful when it speaks the language of the operation using it — the activities, the thresholds, the safety constraints and that sector’s calendar. That is why scoping comes before the contract, and the demonstration runs on a real slice of your operation.

Who builds it

Climate science, remote sensing and software engineering in the same team — and it is that combination that lets us own the models instead of reselling somebody else’s forecast.

25+ years: of senior technical experience
ITA: and Environmental Physics in the team’s background
CBERS: the Brazilian space programme, in the résumé
4: proprietary products in operation

Where we have been

Before we were a product company, we were a team in the crisis room. That is where what we build comes from.

Power utilities

Real climate risk cases over transmission assets in operation.

Rio Grande do Sul

National response to the climate disaster.

2024 wildfire crisis

Supporting the fire brigades through the emergency.

São Paulo and Santos civil defence

Joint monitoring and response operations.

Clients

Agribusiness, engineering, geospatial technology and international organisations — the same decision machinery, in contexts that look nothing alike.

Technology partners

We do not rebuild what already exists and works. The geospatial foundation, the sensors and the cloud come from the people who do it best — and that is what our models run on.

How we treat numbers

These are engineering rules, not marketing ones — they live inside the platforms’ code, and they are why our results survive an audit.

AI explains, the engine decides

In regulated domains, risk classification is deterministic, versioned and auditable. AI agents write the technical and executive readings and guide the decision — without ever classifying the risk. That is the architecture that survives the auditor.

No number on screen is invented

If the source does not publish a field, it stays absent — not zeroed, not blank, not derived from a plausible formula. Zero looks honest and is a trap: “0 mm accumulated” reads as “it did not rain”, when the fact was “nobody measured”.

Uncertainty is part of the number

A projection without a percentile band and without model agreement is half the information. We would rather ship the band, even when it is wide — especially when it is wide.

Every disclosable number carries its origin

Dataset, calibration, how many models were used, how many cells. Without provenance, a number does not survive the auditor’s second question.

Source coverage is declared

When an asset falls outside the footprint of the source feeding it, the platform says so — instead of silently displaying demonstration data.

Alerts follow the operator’s criteria

When the client already has defined thresholds — the same ones their civil defence uses — the alert follows those, not ours. Two systems raising different alarms about the same rainfall is worse than no alarm at all.