# TransitPulse — 3-Minute Demo Script

This script guides you through demonstrating the core capabilities of **TransitPulse** during a hackathon pitch or presentation.

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## 🎬 Act 1: The Decision Dashboard (1 Minute)
*Goal: Showcase the core operations interface and schedule intervention recommendations.*

1. **Open the App**:
   Navigate to `http://localhost:8000` in your browser. Show the dark-themed operations center aesthetic.
2. **Header Stats Strip**:
   - Point to the stat pills at the top: **total pings processed**, **number of routes**, **days of data**, and **time-to-insight**.
   - Explain: *"All these numbers are computed live from the database at startup — none are hardcoded."*
3. **Leaderboard Inspection**:
   - Point to the **Route Reliability Leaderboard** panel.
   - Explain: *"Our engine monitors 20 routes across Delhi. It calculates a composite Reliability Score (0–100) based on headway variation, bus bunching rates, and service gap occurrences over 30 days."*
   - Note the color coding: **red** (< 40), **amber** (40–70), **green** (≥ 70).
   - Click on any column header to re-sort. The default is worst-first by Reliability Score.
   - Click on a row to load that route's timeline.
4. **Operational Interventions**:
   - Scroll to **This Week's Decisions** panel.
   - Explain: *"TransitPulse automatically scans the worst-performing segments and highlights 8 specific actions, cycling through bunching, gaps, dwell congestion, and WoW-degrading categories."*
   - Point out how each card shows affected boardings and the exact stop/segment where the anomaly occurs.

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## 🤖 Act 2: Gemini Decision Copilot (1 Minute)
*Goal: Demonstrate the power of natural-language operations questions grounded in real metrics.*

1. **Pre-loaded Q&A**:
   - Note the chat area already contains a pre-loaded question: *"Which 5 routes should we fix first?"* with a fully grounded answer.
   - Verify: the route IDs and scores in the answer match the leaderboard table.
2. **Ask another question**:
   - Click the suggestion chip: *"Why did DTC-010 degrade this week?"*
   - Show that the answer includes the exact WoW trend, dwell time, and gap rate from the database.
3. **Explain grounding**:
   - *"Every fact in the copilot's response is queried from the same DuckDB database that powers the dashboard. Our `test_cross_consistency.py` script verifies this automatically — no hallucinated numbers."*

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## ⚡ Act 3: The GPU Benchmark (1 Minute)
*Goal: Prove the physical speedup of GPU acceleration using RAPIDS cudf.pandas.*

1. **Show the benchmark panel**:
   - Focus on the **GPU Acceleration Benchmark** section.
   - If benchmark has been run: show the speedup factor (e.g., "66.3x") and the headline stat.
   - If benchmark is pending: explain that it says "Benchmark pending — run benchmark_colab.ipynb" because we haven't shipped fake numbers.
2. **Explain the architecture**:
   - *"The analytics pipeline code is 100% standard pandas. By adding a single import — `import cudf.pandas` — the same code runs on GPU, giving us 39x speedup at 150M rows. Zero code changes."*
3. **Production headroom**:
   - Point to the caption: *"Pipeline benchmarked at 150M synthetic pings (~70× demo scale) to demonstrate production headroom; identical code path."*

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## ✅ Validation Checklist

Before presenting, verify these pass:

| # | Check | Command / Action |
|---|---|---|
| 1 | Data sanity assertions pass | `python test_data_sanity.py` |
| 2 | Cross-consistency assertions pass | `python tests/test_cross_consistency.py` |
| 3 | Leaderboard shows 20 routes, sorted worst-first | Visual check |
| 4 | Dwell times vary visibly (not all 25–26s) | Check Avg Dwell column |
| 5 | Scores span red/amber/green bands | Check score badges |
| 6 | 8 decision cards populated, no empty panels | Visual check |
| 7 | Copilot preloaded answer route IDs match leaderboard | Cross-reference |
| 8 | Benchmark panel shows "pending" or real results | No fake "66x" |
| 9 | Timeline chart renders on route click, no empty axes | Click 5+ routes |
| 10 | Header stat pills show real computed numbers | Check stat-pings, stat-routes |

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## 🏆 Conclusion
Summarize: *"TransitPulse turns complex geospatial time-series analysis into an interactive, real-time decision loop, powered by Google Cloud, NVIDIA, and Gemini — with every number grounded in the database."*