Process mining platform using AI to identify operational inefficiencies
UpFlux builds process mining software that uses AI to surface hidden inefficiencies in operational workflows. The stack reveals a data-heavy org—SQL, Python, Pandas, NumPy, Polars layered across Pentaho and SAP/Oracle systems—suggesting they're extracting and transforming process logs at scale. Active hiring skews toward data (3 roles) and engineering (2), paired with ongoing work on ETL reliability and procurement process implementation, indicating they're scaling data ingest and expanding horizontal use cases beyond the initial process-mining surface.
UpFlux is a process mining platform serving mid-market and enterprise operations teams in Brazil and beyond. The core product analyzes process execution logs using AI to detect bottlenecks, redundant steps, and compliance gaps that manual inspection misses. The company is actively expanding into procurement process automation, with concurrent projects spanning client integrations, go-to-market materials, and value-discovery POCs. Operations are centered in Jaraguá do Sul, Santa Catarina; the 201–500 employee count supports a mid-stage scaling phase with steady hiring velocity.
UpFlux uses Python, SQL, Pandas, NumPy, Polars for data processing; Pentaho for ETL; SAP, Oracle, Coupa, Ariba for enterprise system integration; and MongoDB, AWS, Azure for infrastructure and storage.
UpFlux is headquartered in Jaraguá do Sul, Santa Catarina, Brazil, and currently hires exclusively within Brazil.
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