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

The receipts 🧾

Every red flag on this statement, in full. These are the four places it bites.

1. Exhibit A

   Document question-answering is now an extremely common submission and a generic chat-over-PDF build will be indistinguishable from many others in the room

2. It gets worse

   The real difficulty is table extraction from degraded scans where a misread digit silently produces a wrong tonnage, and a system that answers confidently with a wrong number is worse than one that declines

3. Still reading?

   Parliamentary questions demand exactness and attribution, so any answer without a verifiable citation to source page defeats the purpose — grounding is the requirement, not a nice-to-have

4. And the finisher

   A word cloud module is asked for alongside a query system and it adds nothing analytically; build it because it is specified, but do not let it near your demo

The damage report 📉

Every score this statement earned, and what each one actually costs you.

• Feasibility

  4/5

  Actually buildable, which on this slate is rarer than it sounds. Do not squander it on scope.

  Coal India and CMPDI publish annual reports, production statistics and provisional figures openly, so you can assemble a genuine corpus of exactly the document types the statement describes, and OCR, table extraction and grounded retrieval over PDFs are all mature and well-supported.

• Innovation scope

  3/5

  Mildly interesting. The novelty will not carry the room; the build has to.

  Three modules are named but nothing about their implementation is prescribed, so the extraction strategy, the grounding mechanism and the report generation approach are open, though the overall shape as a document-query system is fixed.

• Clarity

  3/5

  Clear enough to start, vague enough to drift. Write the scope down and stop reinterpreting it weekly.

  The three desired outcomes are listed but the statement is loose around the edges — 'any other production figures' leaves the corpus undefined, a word cloud module sits oddly beside a query system, and the benefit metrics are written as unbounded aspirations rather than targets.

• Acceptance potential

  3/5

  Middle of the pack. This statement will not win the room for you — you will have to.

  Real public documents, a tractable scope and a demo that works reliably are all in its favour, but document question-answering is now among the most submitted shapes at any hackathon, so your standing depends entirely on doing traceable numeric extraction properly rather than shipping another chat interface.

• Effort

  Medium

  Manageable — which means the bar for polish just went up, because you have no excuse left.

  The core is an ingestion pipeline, a structured store and a grounded query interface, all of which are well-trodden with strong libraries; the only genuinely fiddly part is reliable table extraction from poor scans, and the statement asks for three modules rather than a dozen.

• Demo-ability

  Easy

  Easy to demo — and so is everyone else's. Working is the floor here, not the achievement.

  Asking a question in plain English and clicking through to the highlighted table cell in a scanned annual report is instantly convincing and requires no domain knowledge from the judge.

• Data

  None supplied

  No dataset comes with this one, so every accuracy figure you quote is a number about labels you invented.

  Nothing is provided with the statement. You are sourcing, cleaning and labelling it yourself, and that work is invisible in the demo but very visible in the questions.

The demo they will have already seen 🪞

Somewhere around 160–360 teams are heading here, and the description is doing the choosing for most of them. They will read the same brief, reach the same architecture, and build a version of the same demo you are planning. Being correct is the floor. If your five minutes could be swapped with the team before you and nobody in the room would notice, you have not picked badly — you have built predictably, which costs exactly the same and hurts more.

What survives 🛡️

The ground worth standing on when the questions start.

• Coal India and CMPDI publish exactly the document types described — annual reports, production statistics, geological summaries — so your corpus is real and downloadable rather than mocked
• Numeric figures are objectively checkable, which means you can report extraction accuracy against a hand-verified sample and make correctness rather than fluency your claim
• Filed under Miscellaneous, so it will not appear for anyone filtering by a substantive theme