DEMO_VIDEO_SCRIPT.md

Gridlock — Demo Video Script (3–4 minutes)

A scene-by-scene shooting script for the demo video. Each scene gives you: [SHOW] what's on screen · [SAY] the voiceover (≈150 wpm) · [TEXT] on-screen captions/callouts · [TIME] running length.

Total target: ~3:30. Tighten by trimming Scene 6 (Top Areas) or the Models deep-dive if you run long. Record the screen at 1080p+, do a dry run of every click first, and pre-fill the Predict form so you're never typing on camera.

Tone: confident, fast, product-demo energy. Let the app do the talking — narrate the decision, not the UI mechanics ("now I click this button").

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PRE-PRODUCTION CHECKLIST (do this before recording)

• App running and warm (open it once so the model is loaded — first predict can be slow).
• Browser in a clean window, no bookmarks bar, 100–110% zoom, dark OS theme.
• Pre-decide the demo event so the result is impressive and consistent: event_cause = construction, location near HAL Old Airport Road, a weekday evening time. (Construction reliably yields HIGH manpower + closure-likely + chronic-hotspot flag — a strong, story-friendly result.)
• Have a second event ready (e.g. pot_holes at J.P. Nagar) if you want a contrast.
• Map tab pre-loaded once so tiles are cached.
• Screenshots/figures ready as cutaways: reports/figures/*.png, the architecture diagram (export the Mermaid from the deck), and a 1-line dataset stat card.
• Optional: a webcam talking-head bubble in the corner for the intro/outro only.

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SCENE 1 — HOOK + PROBLEM · [TIME 0:00–0:25]

[SHOW] Cold open on the dark Map tab of the live app, slowly zoomed on Bengaluru with hotspot markers glowing. (Don't show the title card yet — open on the product.)

[SAY]

"Every day, a city traffic-control room faces the same questions when an event is reported: do we close this road? Divert traffic? How many officers do we send — and how long will it tie up the corridor? Today, those calls are made reactively, on experience. By the time the response is right-sized, the jam has already spread."

[TEXT] (lower third, fades in/out)

• "Bengaluru · 8,000+ road events"
• "The decisions are reactive. The data could make them predictive."

[TIME] 25s

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SCENE 2 — THE SOLUTION (title beat) · [TIME 0:25–0:45]

[SHOW] Quick, clean title card: "Gridlock — forecast the impact, pre-position the response." Then cut to the Predict tab empty form.

[SAY]

"This is Gridlock. The moment an event is reported, it forecasts four things — and turns each one into a concrete action: a manpower level, a closure-and-diversion call, a clearance time, and an early warning for spots that keep reoffending. Let me show you."

[TEXT]

• "Gridlock"
• "4 forecasts → 4 decisions, in one click"

[TIME] 20s

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SCENE 3 — LIVE PREDICTION (the core demo) · [TIME 0:45–1:35]

[SHOW] The Predict form. Pick a police station from the dropdown → the map pin and coordinates auto-fill (call this out — it's a nice touch). Set event_cause = construction, event type, a weekday-evening start time, a short description ("Metro construction, lane blocked"). Click Forecast. Let the result panel render.

[SAY]

"I only enter what's actually known when an event is reported — the location and start time are required; everything else just sharpens the forecast. I'll pick a spot on Old Airport Road, mark it as construction, and forecast."

(result appears)

"Instantly, Gridlock returns a decision panel, not raw numbers. Up top: the recommended manpower level — HIGH — with a suggested officer count. Then the closure probability with an expected-closure badge, the operational priority, the clearance time with an 80% confidence band, and a chronic-hotspot flag for this location. It even spells out the barricading and diversion plan and a one-line rationale."

[TEXT] (callout arrows on the panel as you mention each)

• "Manpower tier + officers"
• "Closure probability (calibrated)"
• "Duration + 80% interval"
• "Chronic-hotspot flag"
• "Recommended action + rationale"

[TIME] 50s

Tip: Hover one (i) info popover for half a second so viewers see every metric is self-explaining. Don't read it aloud — just let it appear.

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SCENE 4 — WHY IT'S TRUSTWORTHY (the differentiator) · [TIME 1:35–2:05]

[SHOW] Cut to a half-screen: keep the result panel on one side; on the other, drop a simple "leakage caught" caption card (a static graphic you make), e.g.: "Strongest raw predictor scored AP ≈ 0.98 → it was the answer leaking in → deleted on purpose." Optionally flash the architecture diagram briefly.

[SAY]

"Here's what makes this more than a hackathon model. The dataset shipped with no impact label — we engineered all four targets ourselves. And it was full of leakage: the single strongest predictor of a closure was a feature that only exists because the closure already happened. We deleted our most powerful feature on purpose — because using it would be cheating. Every feature Gridlock uses is causal: each event only ever sees events reported before it."

[TEXT]

• "No label existed → we engineered 4 targets"
• "Deleted our strongest feature → it was leakage"
• "Every feature is causal · train on the past, test on the future"

[TIME] 30s

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SCENE 5 — THE MAP (city-scale intelligence) · [TIME 2:05–2:35]

[SHOW] Switch to the Map tab. Click through the four views: Congestion → Chronic hotspots → Closure risk → Manpower load. Hover one station marker so the stat popup shows. Linger on Chronic hotspots (the ~110 m cells) since it's your unique model.

[SAY]

"Zooming out, the same engine powers a city-wide view. Toggle between congestion density, chronic hotspots — the ~110-metre spots likely to reoffend — closure risk, and predicted manpower load. This is the difference-maker: instead of repeatedly patrolling the same junction, the control room sees exactly where to send a permanent fix — drainage, resurfacing, a marshal."

[TEXT]

• "4 city views: Congestion · Hotspots · Closure · Manpower"
• "Chronic hotspots → fix the spot, don't re-patrol it"

[TIME] 30s

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SCENE 6 — TOP AREAS + MODELS (proof) · [TIME 2:35–3:05]

[SHOW] Quick cut to Top Areas — click a column header to sort (e.g. by risk or closure rate) so the re-sort animates. Then a fast cut to the Models tab: scroll past the PR / calibration / SHAP charts and the operating-points table. Keep this snappy — it's a montage, not a walkthrough.

[SAY]

"Every police-station area is ranked and fully sortable, so commanders can find the worst corridors in two clicks. And we don't ask anyone to take our word for it — the Models tab is the evidence: precision-recall and calibration curves, feature importance, and the operating points that let you dial risk posture up for a VIP day, or down for routine ops. Same model, different stance."

[TEXT]

• "Every area ranked · fully sortable"
• "Calibrated, explainable, policy-aware"

[TIME] 30s

If running long: cut the Top Areas beat and keep only a 6-second Models montage.

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SCENE 7 — CLOSE (impact + it's live) · [TIME 3:05–3:30]

[SHOW] Pull back to the Predict result panel or the dark Map. End card with the live URL / QR code and the tagline.

[SAY]

"Gridlock turns a messy, unlabeled event log into foresight a control room can act on — calibrated, honest, and already deployed live, running on CPU with no GPU bill. It doesn't just predict traffic. It tells a city where to stand before the jam forms."

[TEXT]

• "Live now → " (add a QR code)
• "Gridlock · forecast the impact, pre-position the response"

[TIME] 25s

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FIGURES & CUTAWAYS TO PREPARE (referenced above)

Cutaway	Where it's used	Source
Dark Map screen-capture (intro)	Scene 1, 7	live app, Map tab
Title card	Scene 2	make in deck/Canva
Predict result panel (with callout arrows)	Scene 3	live app + annotate in editor
"Leakage caught" caption card	Scene 4	static graphic (1 line of text)
Architecture diagram (brief flash)	Scene 4	export Mermaid from the deck (mermaid.live)
PR / calibration / SHAP plots	Scene 6	reports/figures/*.png
End card + QR to live URL	Scene 7	make in deck/Canva

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TIMING SUMMARY

Scene	Beat	Length	Cumulative
1	Hook + problem	0:25	0:25
2	Solution / title	0:20	0:45
3	Live prediction	0:50	1:35
4	Why it's trustworthy	0:30	2:05
5	Map	0:30	2:35
6	Top Areas + Models	0:30	3:05
7	Close	0:25	3:30

Word budget: 520–540 spoken words total at ~150 wpm ≈ 3:30. If you narrate faster (165 wpm) you'll land closer to 3:00, leaving room for silent UI beats.

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DELIVERY TIPS

• Pre-fill and rehearse the Predict form off-camera; on camera just pick the station and click Forecast so there's no dead typing time.
• Cut on motion — switch scenes right as a panel renders or a sort animates; it keeps pace.
• Narrate decisions, not clicks. Say "the recommended manpower is HIGH," never "I click the predict button."
• Captions on: many judges watch muted first — the [TEXT] lines carry the story alone.
• One impressive result > three mediocre ones. Lock the construction event so the demo is repeatable and always lands HIGH/closure/hotspot.
• End on the live URL/QR and hold it for 3 seconds so judges can open it themselves.