Automated analysis of exploration and mining reports

Purpose

1.1. Automate the end-to-end analysis of exploration and mining reports for consultants, enabling automated extraction, aggregation, and reporting of geological, geophysical, geochemical, and operational data from a range of source documents.
1.2. Automates classification of findings, risk assessments, regulatory compliance checks, and data visualization to support actionable insights.
1.3. Accelerates due diligence, resource estimation, and operational decision-making through repeatable automation workflows that minimize manual data handling and automate data-driven report generation.

Trigger Conditions

2.1. New exploration or mining report uploaded to a data repository (e.g., cloud storage, email inbox).
2.2. API notification or webhook signaling availability of new datasets from field operations or laboratories.
2.3. Scheduled batch automation (e.g., automate nightly scan and report extraction).
2.4. Manual initiation by consultants seeking rapid report processing.

Platform Variants

3.1. Microsoft Power Automate
• Feature/Setting: Configure "When a file is created in SharePoint" trigger, link to custom AI Builder model for document data extraction.

3.2. AWS Lambda
• Feature/Setting: Automate event-driven pipelines triggered by S3 upload; use Textract for automated extraction of tables and text.

3.3. Google Cloud Functions
• Feature/Setting: Automatedly process document ingestion from Google Drive using Vision API and Natural Language API.

3.4. Zapier
• Feature/Setting: Automate "New Attachment in Gmail" triggers followed by document parser integration.

3.5. UiPath
• Feature/Setting: Automate desktop scraping of legacy document management systems; orchestrate automated data transformation.

3.6. Alteryx
• Feature/Setting: Automate workflows for text parsing and geospatial analysis from exploration data sets.

3.7. Apache Airflow
• Feature/Setting: Managed scheduled automator for reporting pipelines; use custom Python operators for report parsing.

3.8. IBM Watson Discovery
• Feature/Setting: Automate unstructured mining document analysis using data enrichment and entity extraction APIs.

3.9. Azure Cognitive Services
• Feature/Setting: Automate document intelligence and OCR pipelines targeting mining report segments.

3.10. Docparser
• Feature/Setting: Automate template-driven extraction of tabular mining results from PDF reports.

3.11. Knack
• Feature/Setting: Automate data mapping from parsed reports to custom database schemas.

3.12. DataRobot
• Feature/Setting: Automate risk and trend prediction models directly on extracted mining features.

3.13. Smartsheet
• Feature/Setting: Automate row creation for each new assay or sample result in standardized sheet layouts.

3.14. Tableau
• Feature/Setting: Automate ingestion of parsed data for real-time geospatial visualization dashboards.

3.15. Qlik Sense
• Feature/Setting: Automate ETL from mining report repositories to automate standardized reporting suites.

3.16. ElasticSearch
• Feature/Setting: Automate indexing and quick lookup of full-text mining documents.

3.17. M-Files
• Feature/Setting: Automate document lifecycle management, including automated metadata extraction.

3.18. Kofax
• Feature/Setting: Automate intelligent document processing and OCR automation for legacy mining reports.

3.19. Power BI
• Feature/Setting: Automate scheduled dataset updates and real-time mining metrics dashboards.

3.20. SAP BusinessObjects
• Feature/Setting: Automate report scheduling and automated KPI extraction from incoming data feeds.

Benefits

4.1. Accelerates reporting and analysis cycles through automated data workflows.
4.2. Reduces manual errors by automating data parsing and report extraction.
4.3. Enables scalable, repeatable automation of large volumes of mining documents.
4.4. Ensures consistent regulatory compliance through standardized automated checks.
4.5. Improves consultant productivity with rapid data-driven insights powered by automation.