Intelligence so hidden faults never become unplanned downtime.
An asset can fail in the gap between human checks. Datamint exists to eliminate those gaps — with the engineer deciding every case.
How we got here
Founded in 2021, from a Rio de Janeiro research group.
Datamint began inside a university lab studying how to give industrial software something closer to engineering judgment: a structured model of an asset, and the ability to reason over it. The work moved out of the lab, into production environments at industrial operators, and into a company.
Who built it
Connecting research, operations, maintenance, and tangible results.
PhDs anchored the technical foundation. A builder was brought in to ship it.
What we research
Five disciplines, one platform.
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Artificial Intelligence
Models that learn from sensor and operations data to detect faults and predict asset behavior.
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Ontology
Your raw field data gains structure: equipment, failure modes, and operating conditions — organized and ready to generate value.
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Agentic Workflows
Systems that perceive, analyze, and enable action across continuous industrial operations, without interruptions.
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Decision Governance
From review to approval, every action is recorded and traceable.
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Human–AI Interaction
Engineers in control, AI transparent: see the reasoning behind every recommendation.