A formal water management pilot at an operational site: process mapping, water balance with data accuracy, KPIs, instrumentation plan, and consolidation into an AI agent.
The core challenge was to transform water management at a complex mining site into a mapped, measurable, and auditable process capable of supporting stronger governance and, subsequently, AI-assisted operations.
1. Current process mapping
Inputs, outputs, storage, main flows, stakeholders, and information flow across databases, emails, presentations, and reports.
2. Water balance with accuracy and KPIs
Balance calculation, data accuracy statement, and definition of traceable indicators.
3. Monitoring and instrumentation plan
Definition of measurement points, frequencies, automation, and prioritized instrument CAPEX.
4. Consolidation into an AI agent
Preparation of data, workflows, and interfaces for operations assisted by a dedicated water management AI agent.
- Planning and initial engagement.
- Data collection and assessment.
- Operational implementation and testing.
- Evaluation and final adjustments.
- As a strategy to advance operational water management maturity in 2025, Data Riders was engaged to launch a pilot at a major mining complex.
- Four objectives are documented: map the current process; calculate the site water balance, including data accuracy and KPIs; develop a monitoring and instrumentation plan; and consolidate the process into the development of an AI agent.
- The kickoff materials organize the work into four phases: planning and initial engagement; data collection and assessment; operational implementation and testing; and evaluation and final adjustments.
- The program explicitly covers proof of concept, implementation, training, support, data reliability, indicators, and reporting.
Sources: pilot tracking report and water resources kickoff deliverables (internal Data Riders material, client kept anonymous).
Structured a formal pilot with process and document mapping, stakeholder mapping, water balance calculation, KPI definition, instrumentation planning, and AI agent preparation. More than an analytical study, it was an operational transformation program.
Bridge between assessment and implementation: made data, monitoring, and governance actionable for day-to-day decisions.
Talk to Data Riders about water management pilots with water balance, KPIs, instrumentation, and AI agents.
