An intelligent operating system for urban social governance and public-service scenarios.
HetuOS focuses on the full loop of discovery, analysis, dispatch, response, and review in urban governance. It structures multi-source governance data and combines intelligent analysis, cross-agency collaboration, traceable processes, and feedback loops so AI can support real public-service work.
Grassroots governance rarely lacks system entry points; the harder problems are inconsistent data definitions, unclear responsibility chains, and weak review of response processes. HetuOS places AI inside the governance workflow to support event understanding, evidence organization, and coordinated response.
The project designs capabilities for data integration, event labeling, risk analysis, response suggestion, cross-agency dispatch, and process logging. It combines knowledge bases, rules, model analysis, and human confirmation so automation does not detach from governance accountability.
The project has produced a system framework and scenario prototypes for intelligent urban governance, supporting multi-source data integration, event loops, and collaborative response. It remains ongoing, with work continuing on governance knowledge, explainability, and scenario evaluation.