Project idea
Predict leaks from network sensor data and inspections.
Mawj AI | SweTech Products
SweTech Products · ST-AI-10241
Mawj AI
Predict leaks from network sensor data and inspections.
AI stack: Time-Series AI + Anomaly Detection + GIS
Project details
Business need
Utilities teams currently lose time to fragmented tools, manual review and slow decision cycles around water leak detection.
Solution overview
Mawj AI is an AI-first water leak detection product designed to predict leaks from network sensor data and inspections.
Intended users
Operational users, supervisors, managers and enterprise administrators Primary users are Operational users, supervisors, managers and enterprise administrators; secondary stakeholders include supervisors, auditors, administrators and decision makers.
Core workflow
The core workflow connects Live Map, Layer Control, Zone Detail, Route / Navigation with notifications, reports, audit history and role-based approvals.
AI capability
Time-Series AI + Anomaly Detection + GIS AI is used through Time-Series AI + Anomaly Detection + GIS to turn raw operational input into findings, explanations, recommendations and executable workflow steps. Optional orchestration layer for automating approved workflow steps. Not core; camera input may support evidence capture only.
Data, integrations and deployment
Data layer combines User input, enterprise systems, operational records, approved knowledge sources; analytics surface trends, exceptions, confidence, workload and operational performance. Integrations: REST APIs, SSO, notifications, reporting/export, GIS services. Keep integration states visible with sync status, source attribution and audit history. On-premises, private cloud or hybrid; edge deployment where latency/privacy requires it
Arabic and user experience
Bilingual-ready; Arabic RTL recommended for GCC deployment; use clear Arabic labels, RTL navigation, bilingual data fields and culturally neutral contemporary design. UX should prioritize a light premium interface, fast task entry, clear AI evidence, readable cards, realistic maps/charts and responsive mobile/web layouts.
Security and observability
RBAC, audit trail, encryption, data minimization, tenant isolation, human approval for sensitive actions Model telemetry, prompt/run logs, latency, cost, confidence/quality metrics, user feedback
Expected business value
Expected value: Reduce manual work, accelerate decisions, improve traceability and create measurable operational intelligence. Success is measured with Adoption %, task completion time, AI acceptance rate, exception rate, response time, accuracy/precision where applicable.
Illustrative design and folder setup only. Screens, architectures, and prompts in this package are proposed planning material; final visuals and technical behavior still require review. Do not present this illustrative material as a real client deployment. This page presents illustrative material, not a confirmed client deployment or a performance guarantee. Validate scope, data access, privacy, security and model behavior before implementation.