Between diagnostic reports and real operational change, there is usually a gap. Data Riders ran a formal water management pilot at a mining site to bridge that gap — turning diagnostics, monitoring and governance into something usable in day-to-day decisions.
Four-block approach
1. Current process mapping
Inputs, outputs, storage, main flows, stakeholders and information flow across databases, emails, presentations and reports.
2. Water balance with precision & KPIs
Balance calculation, data-precision statement and definition of traceable indicators.
3. Monitoring & instrumentation plan
Measurement points, frequencies, automation and prioritized instrument CAPEX.
4. Consolidation into an AI agent
Data, flows and interfaces prepared for operation assisted by a dedicated water-management AI agent.
Four working phases
- Planning and initial engagement.
- Data collection and diagnosis.
- Operational implementation and testing.
- Evaluation and final adjustments.
Verified, source-backed facts
- As a strategy to raise the operation's water management maturity in 2025, Data Riders was hired to start a pilot at a large mining complex.
- Four pilot objectives are documented: map the current process; calculate the site water balance including data precision and KPIs; develop a site monitoring/instrumentation plan; consolidate the process into development of an AI agent.
- The kick-off material organises the work into four phases: planning and initial engagement; data collection and diagnosis; operational implementation and testing; evaluation and final adjustments.
- The program explicitly covers proof-of-concept development, implementation, training, support, and data reliability, indicators and reporting.
Sources: pilot follow-up report and water-resources kick-off deliverables (internal Data Riders material, client kept anonymous).
What Data Riders did
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 — an operational transformation program.
Documented value
A bridge between diagnosis and implementation: data, monitoring and governance made usable in day-to-day decisions.
Related reads, cases and services
- Case: Water-governance maturity diagnostic
- Case: Water KPI tree aligned with WAF
- Case: AI agent for water balance and governance
- Case: Intelligent water diagram and stakeholder mapping
- Service: Water Management with AI
- Blog: Document Intelligence in mining
Editorial note. The pilot objectives, phases and scope are documented. KPI values, instrumentation counts and post-pilot results will be added when released by the client for external publication.