In many operations, tailings governance programs still depend on fragmented documents, manual evidence collection and slow conformance reviews. GISTM.ai, developed by Data Riders, addresses that problem head-on: it turns documentation, evidence and compliance checks into a continuous, AI-assisted flow.
The business challenge
Adherence to the Global Industry Standard on Tailings Management (GISTM) is today the international benchmark for dam safety and tailings management. In practice, operations face three persistent pain points:
- Evidence scattered across multiple systems, folders and spreadsheets.
- Long, expensive audits concentrated in specific windows of the year.
- Low visibility on the actual effectiveness of controls between audits.
GISTM Principle 11 — focused on communication, continuous learning and early problem identification — reinforces the need for a living governance model, not just an annual report.
Verified, source-backed facts
- GISTM.ai is a platform developed by Data Riders to apply artificial intelligence to adherence with the Global Industry Standard on Tailings Management — with explicit attention to Principle 11: communication, continuous learning and early problem identification.
- The platform collects and processes large volumes of operational and technical data in real time, enabling predictive and dynamic management of risks related to dams and geotechnical structures.
- At launch, GISTM.ai was presented as an intelligent audit platform for GISTM conformance, positioned as a way to reduce the complexity, time and cost of audit processes across the 77 GISTM requirements.
- Two deployment patterns are documented: managed SaaS and dedicated/private deployment on AWS, with security and privacy layers fit for enterprise customers.
Sources: Data Riders internal case pack, GISTM.ai launch materials and GISTM.ai Security & Privacy Overview. Client-approved metrics, screenshots and quotations will be added after validation.
What Data Riders did
Data Riders designed, built and operates GISTM.ai as an intelligent audit platform for GISTM compliance. The product combines three layers:
Evidence processing
Ingestion and analysis of large volumes of operational and technical data to automatically map evidence to the 77 requirements of the standard.
Gap identification
Automated analysis that flags gaps, outdated evidence and points requiring priority action — without waiting for the next audit cycle.
Security and deployment
Two operating models: managed SaaS and dedicated private-cloud deployment, with security and privacy layers fit for corporate contexts.
Architecture and core capabilities
- Mapping of the 77 GISTM requirements with evidence traceability by principle and requirement.
- Executive dashboard showing compliance status, critical gaps and trends over time.
- Audit reports generated with methodological consistency and reduced preparation time.
- Intelligent alerts on expiring evidence, weak controls and requirements with low coverage.
- Continuous learning aligned with the spirit of GISTM Principle 11.
Documented value
- Safer, more auditable operations with always-up-to-date evidence.
- Stronger knowledge management, connecting technical teams and leadership.
- Reduced complexity, time and cost of audit processes.
- Lower dependency on fragmented systems and long review cycles.
Why this case matters
GISTM.ai combines mining governance expertise with applied AI engineering, moving compliance from a periodic model (sampling-based audits) to a continuous one (live assurance). It is a practical example of how Data Riders integrates method, international standards and technology — a tripod that also appears in other cases in this collection.
Related reads, cases and services
- Case: AI-assisted GISTM audit and gap identification
- Case: Reliable Assurance framework and Health Index
- GISTM.ai — compliance platform
- Service: AI Solutions & Document Intelligence
- Service: Audit & Compliance
- Blog: GISTM.ai launch
- Blog: Document Intelligence in mining
Editorial note. This case study is intentionally conservative. It includes only what is directly supported by Data Riders' internal source material (case pack, launch assets and Security & Privacy Overview). Specific client-approved outcomes, metrics, quotations or product screenshots may be added in future updates as they are released for external publication.