An AI agent that connects assets, flows, people, and technology for predictive, auditable, and integrated water management under the MCA-WAF standard.
Water governance in mining is often slowed down by emails, spreadsheets, field data, and fragmented audit trails. The AI agent developed by Data Riders acts as the integration layer across these touchpoints, focusing on water balance, traceability, and real-time decision-making.
Field data capture
Dam levels, inflows and outflows, groundwater and surface abstraction, climate and operational data.
Advanced analytics
Validation, classification, and continuous inference of water balance under MCA-WAF.
Decision support
Direct support for strategic and operational decisions, with end-to-end traceability.
- Data Riders developed a dedicated AI agent for water management, capable of advanced operational analysis of the water balance and direct support for strategic decision-making.
- The agent is integrated with the international MCA Water Accounting Framework and captures field data such as dam levels, inflows/outflows, groundwater and surface abstraction, and climate/operational data.
- Project materials describe the agent as a connector across assets, flows, people, and technology, enabling predictive, auditable, and integrated water management.
- The agent automates data validation, classification, and analysis for continuous inference of the water balance under the MCA-WAF standard, enabling digital governance and real-time change management.
Sources: internal case study materials; Entrega Ago 25.pptx; Apresentação final.pptx; VGR.pdf; Entrega Junho 2025.pdf.
Designed an AI agent that centralizes data inputs, supports water balance calculation and validation, improves traceability, and connects governance to operational data.
- Faster, more reliable decisions.
- Stronger traceability.
- Greater confidence in disclosed information.
- Digital operating model for water governance.
