PS 26023SOFTWAREMiscellaneousHidden GemFast Prototype (36h)

AI-Powered Geological, Mining and other Reporting Solution for CMPDI/CIL subsidiaries

Ministry of CoalCoal India Limited
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30-Second Plain English Summary

CMPDI and Coal India subsidiaries spend hundreds of manual hours extracting geological borehole data, stripping ratios, and coal production figures from scattered PDFs, legacy spreadsheets, and handwritten field archives to answer high-priority parliamentary questions and statutory inquiries. Build an enterprise Retrieval-Augmented Generation (RAG) and document AI platform combining domain-specific OCR, tabular data extraction, and a deterministic Q&A verification engine.

5-Dimension Strategic ScorecardOverall Score: 3.8 / 5.0
Innovation
3.7 / 5
36h Feasibility
4.3 / 5
Uniqueness
3.5 / 5
Jury Appeal
3.7 / 5
Tech Depth
3.9 / 5
Recommended System Architecture Pipeline
Scanned PDFs & Spreadsheets -> Table Transformer & OCR -> Qdrant Vector Store + Hybrid SQL Engine -> Local LLM RAG with Guardrails -> Parliamentary Response Console
Recommended Tech StackClick to search similar
Official Government Problem Description
Background: CMPDI/CIL subsidiaries play a key role in providing geological and mining information to the Ministry of Coal and responding to parliamentary and high-priority administrative inquiries. These reports require compilation of data from scanned PDFs, digital documents, spreadsheets, images, and historical archives. The current workflow is largely manual, resulting in: • High dependence on individual expertise • Delay in generating reports and analytics • Higher probability of manual errors • Limited ability to quickly retrieve insights when required Objectives: • Deploy an automated platform for AI-assisted geological, mining and any other production figures document processing and reporting. • Enhance data validation, consistency, and traceability across historical and contemporary datasets. • Build an efficient, scalable foundation for future digital transformation initiatives within each CIL subsidiary and the Ministry of Coal. Desired Outcomes: The solution should be implemented in structured phases, including requirement analysis, data digitization and pre-processing, platform development, system testing, integration with CIL subsidiary workflows, training, and continuous enhancement to ensure scalability and long-term adoption. 1. Automated Report Generation Platform 2. Automated Word Cloud and Topic Identification Module 3. AI-Based Query and Response System Expected Benefits: • Reduction in report preparation time as less as it can be, quantified in percentage. • Maximum accuracy, calculated in percentage in structured extraction and report generation. • Maximum automation, calculated in percentage of repetitive reporting and response workflows. • Faster response to high-level inquiries and parliamentary questions • Improved data accessibility, transparency, and standardization • Strengthened operational efficiency and informed decision-making using historical insights and AI-generated recommendations Impact: The proposed system should significantly modernize CMPDI/CIL subsidiaries reporting ecosystem, reduce dependency on manual processes, improve response timelines, and strengthen the coal sector's capability to support governance, policy planning, and operational excellence.
AI & PPT Citation Format

Smart India Hackathon 2026 Problem Statement PS-26023: "AI-Powered Geological, Mining and other Reporting Solution for CMPDI/CIL subsidiaries", Ministry: Ministry of Coal. Strategy & Architecture via SIH ONE (https://sihone.pages.dev/ps/26023)

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