Case Study: a grande rede hospitalar de São Paulo reduces maintenance prioritization time with Agence AI automation

grande rede hospitalar de São Paulo cuts maintenance prioritization time by 40% with Agence

A unit of a grande rede hospitalar de São Paulo was losing significant managerial time as four managers spent 14 hours per week manually prioritizing maintenance orders from their CMMS, a process prone to human error and variability. They engaged Agence to automate this process using IA (Artificial Intelligence) while ensuring the final decision remained with the human managers.

Agence implemented a two-layer solution featuring automated data extraction from the Manusis4 CMMS and a local LLM for semantic analysis and priority classification. This reduced the weekly data preparation time from 4 hours to under a minute and cut management meeting time by approximately 40%. The AI achieved a 72% concordance rate with the managers' final decisions and correctly identified all 18 critical orders during the production test, all while keeping sensitive data secure on the hospital's own infrastructure.