The debate on water supply and waste management is an economic and environmental issue that has been discussed since the earliest cities. Initially, sewage was dumped into rivers without treatment, but with scientific advances, new solutions have emerged. In Brazil, Law No. 11,445/2007 regulates basic sanitation, which includes water supply, sewage, solid waste management, and urban drainage. Investments in this area are essential for public health and sustainable development, but there are still many people without access to these services, which aggravates health problems and environmental degradation, according to UNICEF (2020). Technologies such as artificial intelligence and fuzzy inference systems have been applied to optimize the management of these services. This study developed a fuzzy inference model to assess the quality of basic sanitation services. The model analyzed indicators such as water supply, sewage, and waste management, using the fuzzy methodology to address uncertainties and generate more accurate diagnoses. The process included fuzzification of inputs, application of inference rules, and defuzzification to transform the results into interpretable data. The results demonstrated that fuzzy logic is effective in identifying critical points in sanitation, offering solutions to reduce costs and increase efficiency. The model is adaptable to different regional contexts, facilitating its application in other locations. With this tool, it was possible to direct corrective actions, contributing to the improvement of services and the universalization of sanitation. This supports the fulfillment of Sustainable Development Goal (SDG) 6, which aims to ensure universal and sustainable access to water and sanitation.