# Riprap: landscape research Captured 2026-05-06 as part of the AMD x lablab.ai hackathon polish phase. This document underpins the pitch deck (`slides/deck.md`) and the demo-script choices. Re-validate against the live web before re-using any specific figure. --- ## What Riprap is, distinctly A citation-grounded LLM that writes audit-quality flood-exposure briefings for NYC addresses by fusing live, historical, modeled, and projected data sources. Mellea rejection sampling refuses to publish a numeric claim it can't cite. The output isn't a score. It's a four-section prose briefing with `[doc_id]` citations on every numeric assertion, where each `doc_id` resolves to one specific dataset (Sandy 2012 zone, NYC DEP scenario, USGS HWM, Sentinel-2 chip, NOAA gauge reading, NPCC4 SLR projection). Granite 4.1 8B drives the prose. Granite Embedding 278M plus GLiNER drive policy-doc retrieval. Prithvi-EO 2.0, TerraMind LULC and Buildings, and Granite TTM r2 drive the EO and forecast probes, with three Apache-2.0 NYC fine-tunes trained on AMD MI300X published on HF Hub. Architectural commitments other tools don't make: 1. **Silence over confabulation.** When a probe returns no data, the briefing omits the section rather than papering over it. 2. **Five-stone epistemic structure.** The user can see what's empirical vs modeled vs proxy vs synthetic. 3. **Fully open-source pipeline.** Apache-2.0 end-to-end on public- record data, no commercial APIs touched at runtime. 4. **Deployable on either local Ollama or AMD MI300X via vLLM** with auto-failover. Stack as of 2026-05-06: SvelteKit UI on HF Spaces (cpu-basic) at the AMD-hackathon org, FastAPI agent FSM, two-container droplet (vLLM plus riprap-models) on MI300X, full address probe suite at 5/5 PASS in 5.8 to 13.1 s end-to-end. --- ## Landscape map ### Direct comps: score-based property risk tools | Tool | What it gives | Who it serves | Hidden cost | |---|---|---|---| | **First Street Risk Factor** (Flood Factor) | Score 1 to 10 plus 30-yr risk narrative; powers Redfin, Realtor.com (until Dec 2025 also Zillow) | Homebuyers; some lenders | Closed model; commercial partnerships; Zillow removed it under industry pressure in Dec 2025 | | **ClimateCheck** | Score 1 to 100 plus around 30-page property report; 2050 projections | Homeowners plus REIT/PE diligence | Subscription tiers; methodology behind paywall | | **Jupiter ClimateScore Global** | Enterprise SaaS / API; financial metrics (CapEx, OpEx, credit risk) | Banks, insurers, asset managers | Enterprise pricing; not consumer-facing | | **Cervest / Climate X / ICEYE** | Variants of above for ESG / reinsurance | Corporate finance and insurance | Same | Score-based tools all converge on the same shape: one number, one chart, an explainer paragraph. None show what claim is grounded in which dataset. None expose the audit trail. ### NYC-specific government tools - **FloodHelpNY** (City plus State, IDEO-designed). Address lookup to flood-zone label plus insurance plus free resiliency audit. Forms-based, consumer-facing, doesn't fuse live signals. - **NYC Flood Hazard Mapper.** ArcGIS web map of FEMA, NPCC, Sandy, and future scenarios. Static visualization, no narrative. - **NYC OEM Flood Maps page.** Index of the above. - **EJNYC Flood Vulnerability Index** (released 2024-04 by Mayor's Office of Climate and EJ). First-ever city FVI, used to direct spending under NY's "Disadvantaged Communities" framework (35% of climate spend by law). - **FloodNet NYC** (NYU plus CUNY plus city). Over 350 ultrasonic sensors at 1-min cadence, growing to 500 by end-2026. Has a public dashboard but no narrative layer. ### Federal / authoritative - **FEMA Flood Map Service Center / NFHL.** Official; covers 90%+ of population; static GIS layer plus PDFs. The disclosure-of- record but not a synthesis tool. ### Real-estate platforms (the volatile zone) - **Redfin.** Still shows First Street Flood Factor on every listing. - **Realtor.com.** Still shows it on 110M+ listings. - **Zillow.** Removed climate risk display in December 2025 under California Regional MLS pressure. Still links out, but it's hidden. This created a vacuum that an open citation-grounded alternative could fill. ### Closest academic / AI comps - **Flood-LLM** (Brisbane, MDPI Sustainability 2026). Multi-source LLM for property-level flood risk, validated on Brisbane against official labels. Academic, not deployed; no Mellea-style citation discipline; no live signals. - **GIS-Integrated Flood LLM** (Tandfonline 2024). LLM constrained by a flood knowledge graph plus GIS interaction. Research artefact. - **FloodLense** (arXiv 2024). UNet/RDN/ViT plus LLM for satellite flood detection. Research; image-only. --- ## Where Riprap fits: differentiators that demo well Ranked by visibility in a 3-minute demo: 1. **Citation prose vs scores.** Riprap returns *"Hurricane Sandy flooded this address on October 29 to 30, 2012, according to the empirical inundation zone [sandy]. 19 flood-related 311 service requests were logged within 200 m over five years [nyc311]."* Every number cites a doc; each doc resolves to a footer source row. First Street returns "Flood Factor 8/10". This gap is the demo. 2. **Live, historical, modeled, projected: in one paragraph.** Sandy 2012 (empirical), DEP 2080 stormwater scenarios (modeled), 311 last 5 years (proxy), FloodNet last 3 years (empirical, hyperlocal), NPCC4 SLR (projected), Granite TTM r2 surge nowcast (96-h forecast). No comp combines all four temporal modes. 3. **Open-source NYC fine-tunes.** Three Apache-2.0 models (`Prithvi-EO-2.0-NYC-Pluvial`, `TerraMind-NYC-Adapters`, `Granite-TTM-r2-Battery-Surge`) trained on AMD MI300X. Anyone can reproduce, fork to other cities, or audit. First Street's model is closed; ClimateCheck's methodology is behind a paywall. 4. **AMD hardware story.** The whole stack runs on MI300X via vLLM (LLM) plus a sibling ROCm container (probes). All Apache-2.0. This is the AMD hackathon track's preferred narrative: open models, open infra, open data, real GPU acceleration. 5. **Mellea grounding receipts.** The four checks (`numerics_grounded`, `no_placeholder_tokens`, `citations_dense`, `citations_resolve`) are the audit. The meta card surfaces "4/4 grounding checks passed, 1 reroll". That's audit credibility no consumer comp shows. 6. **Self-aware silence.** Touchstone shows "FloodNet sensor: 0 events in 3 years" with `silent_by_design`. Lodestone shows "TTM Battery surge forecast: peak |residual| < 0.3 m, omitted." Most tools always render a value. Riprap's silence is a feature. --- ## Stakeholder demos to craft Six concrete personas, each with a query that exercises a different part of the system. These are the demo arcs to rehearse. ### 1. Resident / homebuyer (the FloodHelpNY swap-in) > *"I'm thinking about renting an apartment at 80 Pioneer Street, > Brooklyn. Should I worry?"* **Demo arc.** Type the address. Watch the planner classify `single_address`, then 19 step events fire across the four data Stones in around 13 s. Briefing names Sandy 2012 inundation, 65 311 complaints, 2 FloodNet sensors with 4 events including a 51 mm peak on a specific date, Ida 2021 HWM 130 m away, microtopo HAND 3.81 m plus TWI 14.79 (very high saturation propensity). Footer shows 7+ named primary sources. **Demo hook.** "Compare what we just generated to First Street's number-and-bar-chart for the same address. Which would you trust to make a $4,000/month decision?" ### 2. Real-estate attorney / disclosure compliance > *"Does 100 Gold Street, Manhattan need to disclose flood risk > under RPL §462(2)?"* **Demo arc.** Same single_address path. Briefing produces a citable narrative covering FEMA designation, prior flood claims (where present), terrain, recent complaints. Mellea grounding check is the qualifier: "this prose is grounded against four invariants and passed 4/4." **Demo hook.** New York's March-2024 amended Property Condition Disclosure Statement requires sellers to disclose flood history and FEMA-floodplain status. RPL §231-b requires every residential lease to disclose prior flood damage. Riprap is the citable narrative tool. Show how the briefing maps line-by-line to the disclosure requirements. ### 3. NYC OEM / DEP planner > *"Hollis, Queens"* **Demo arc.** Neighborhood intent fires (9 step events), produces an NTA-level briefing. 434 flood-related 311 over 3 years (87 catch- basin clogged, 42 street-flooding), 4.3% of neighborhood projected to flood under DEP moderate-2050 scenario, 25% of cells with HAND<1 m. RAG retrieval pulls relevant DEP/NPCC4 policy paragraphs. **Demo hook.** DEP just announced a $30B stormwater priority list (86 locations) and a $68M Brooklyn Bluebelt expansion in Prospect Park. Riprap supports the prioritization argument with citable per- NTA evidence. Pair with the EJNYC Flood Vulnerability Index for the EJ-spending overlay (35%-to-disadvantaged-communities legal mandate). ### 4. Insurance underwriter / actuary > *"442 East Houston Street, Manhattan"* **Demo arc.** Same as resident demo, but emphasize the **provenance trace** UI. Every Stone row, every doc_id, every source URL, vintage, and tier glyph. **Demo hook.** When an underwriter writes a risk memo, the audit chain matters. First Street's "we used a proprietary catastrophe model" doesn't survive a regulator review the way "we used FEMA Sandy 2012 polygon, NYC DEP 2021 stormwater scenario, USGS Ida HWM Event 312, NOAA gauge 8518750, NWS station KNYC, Granite TTM r2 fine-tune (test MAE 0.1091 m vs 0.1467 zero-shot, citable)" does. ### 5. Climate journalist / advocacy > *"Coney Island, Brooklyn"* **Demo arc.** Neighborhood briefing. 87.5% of NTA in 2012 Sandy zone, 382 flood complaints over 3 years, 7.8% projected flooded under 2050 moderate, 38.9% of DEM cells with HAND<1 m, DEP extreme- 2080 at 44.2% flooded. **Demo hook.** ProPublica/NYTimes/THE CITY-style data journalism. Every claim in a Riprap briefing is reproducible. Anyone can paste the same query and get a near-identical narrative. The journalist can publish the briefing as the methods section. ### 6. Architect / developer > *"What are they building in Gowanus and is it risky"* **Demo arc.** Planner classifies `development_check`. FSM pulls DOB filings plus flood layers for the project sites. Briefing comments on which proposed buildings sit inside Sandy 2012, which intersect DEP extreme-2080, what the microtopo says. **Demo hook.** Pre-design siting check. The Gowanus rezoning is one of NYC's largest active development zones, well known to flood. Show how the tool surfaces flood concerns before architects pour concrete. --- ## Lateral and unexpected use cases Ten bets, ordered roughly from most-buildable to most-speculative. 1. **Pre-storm cohort briefings.** Subscribe Riprap to NWS flood- watch alerts. When a watch lands, fan out one briefing per affected NTA plus push to OEM, press, and advocacy lists. Citable evidence on demand for the press cycle that follows. 2. **Climate-grant evidence sections.** HUD CDBG-DR and FEMA BRIC applications need an auditable evidence base. Riprap auto- generates the "vulnerability assessment" section so a community group can apply for resilience funding without hiring a consultant. 3. **Local Law disclosure boilerplate.** Plug into a brokerage's listing flow. When an agent enters an address, auto-generate the NY RPL §231-b lease addendum or §462(2) disclosure draft. ROI is high since the law took effect 2024 and many landlords are still figuring out compliance. 4. **MTA station-hardening prioritization.** Riprap already has the MTA-entrance probe (KEY-001 in the demo). Run the FSM across all subway entrances; rank by exposure × ridership. The MTA's October-2025 Climate Resilience Roadmap Update is the policy hook. 5. **DOE school siting.** When DOE reviews proposed school sites or selects schools for retrofit, Riprap briefings (with `expect_311_ge` plus Sandy plus DEP overlays) would catch flood exposure that form-style screens miss. 6. **Time-machine variant.** Re-run the FSM with snapshot data from a past date. *"What would Riprap have said about Hollis on August 31, 2021, the day before Ida?"* Useful for retrospective analysis, expert testimony, and stress-testing the system. 7. **Cross-city scaffold.** The architecture is NYC-specific by data choice, not by code. Port to Houston (post-Harvey plus Hurricane Beryl 2024), Miami (king tides), Boston (CSO floods), Charleston (chronic tidal), with a per-city probe set plus RAG corpus. 8. **Federation with FloodNet alerts.** When a sensor triggers a flood event NOW, fire a Riprap live_now briefing for the surrounding NTA: *"what's at stake in the next 6 hours."* Connects FloodNet's hyperlocal sensor reads to the OEM decision loop. 9. **EJNYC × Riprap pairing.** Rank all 188 NTAs by Riprap-detected exposure, intersect with state DAC designations. Output: a map of "underserved plus underwater". The most underfunded high-exposure neighborhoods. 10. **Court testimony / expert witness.** Citable, reproducible flood narrative as a court exhibit. The Mellea passes-record plus provenance trace are the kind of artefact a regulator or judge can audit. Especially relevant after the December-2025 Zillow controversy created public discussion of climate-data integrity. --- ## Risks and framing - **Real-estate industry pushback.** December 2025: Zillow removed First Street's climate scores under MLS pressure because the data was hurting transaction volume. A free, citation-grounded alternative could face the same reflex. Riprap's defence is that it's a narrative tool for professional analytical work, not a buy/don't-buy verdict. Keep the disclaimer footer prominent. - **Redlining hazard.** Exposure narratives can be misused by landlords or insurers to discriminate against high-flood-risk (often disproportionately disadvantaged) neighborhoods. Mitigations: (a) the citation transparency makes biased reasoning auditable, (b) the EJNYC pairing in lateral-use #9 reframes exposure data as a tool *for* affected communities, not against them, (c) keep "for professional analytical work, not personal property decisions" front and center. - **Disclosure-status liability.** A briefing is *evidence* but probably not *the* §462(2) disclosure under New York real-estate law. Don't position it as legal disclosure-of-record without a real-estate-attorney review. - **Cold-start latency.** First query after droplet redeploy is around 30 s while models warm. For demos, ping the Space and run one warm-up query 5 minutes before showtime. - **Geocoder edge cases.** "PS 188, Lower East Side" geocoded to a Brooklyn PS 188 in our test suite. For demos, pick fully-qualified street addresses; document the disambiguation behavior. --- ## Polish punch-list (deck-driven) Concrete polish items the research surfaces, ranked by demo value: 1. **Sample-query pills on landing.** Six clickable pills below the search bar, one per persona above. Let the audience demo themselves. 2. **A "What this is" bar at the top of the landing.** Three lines: *"Citation-grounded NYC flood briefings. Every number cites a primary source. Open-source, public data, audit-grade synthesis."* 3. **Compare-mode link from the briefing.** Once Riprap delivers a single_address briefing, surface "compare with another address" as a one-click affordance. The compare intent already exists in the planner. 4. **EJNYC-FVI overlay** on the map sidebar (#9 above). Riprap's exposure × DAC designation, two clicks to a powerful editorial demo. 5. **First-query warm-up message** during the cold start: *"loading probes on AMD MI300X. First query after redeploy takes around 30 s; subsequent queries 5 to 13 s."* --- ## Sources - [First Street Foundation: Flood Factor methodology](https://firststreet.org/methodology/flood) - [FloodHelpNY: NYC and IDEO consumer tool](https://www.floodhelpny.org/en) - [ClimateCheck: flood risk methodology](https://climatecheck.com/risks/flood) - [Jupiter Intelligence: ClimateScore Global / FloodScore](https://www.jupiterintel.com/climatescore-global) - [FEMA Flood Map Service Center](https://msc.fema.gov/) - [NY State: RPL §231-b residential lease flood disclosure (2023)](https://www.nysenate.gov/legislation/bills/2021/S5472) - [NYSBA: Property Condition Disclosure flood-risk amendment (Mar 2024)](https://nysba.org/breaking-news-new-rules-on-property-condition-disclosure-and-flood-risk-go-into-effect-today/) - [CNN: Zillow removes climate risk data under industry pressure (Dec 2025)](https://www.cnn.com/2025/12/02/climate/zillow-climate-data-extreme-weather-first-street-redfin) - [NYC Stormwater Resiliency Plan](https://www.nyc.gov/assets/orr/pdf/publications/stormwater-resiliency-plan.pdf) - [FloodNet NYC: methodology and sensor network](https://www.floodnet.nyc/methodology) - [FloodNet WRR 2024: peer-reviewed sensor paper](https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2023WR036806) - [EJNYC Report: Mayor's Office of Climate and Environmental Justice](https://climate.cityofnewyork.us/ejnyc-report/the-state-of-environmental-justice-in-nyc/) - [Flood-LLM: Brisbane case study (MDPI 2026)](https://www.mdpi.com/2071-1050/18/6/2957) - [GIS-Integrated Flood LLM (Tandfonline 2024)](https://www.tandfonline.com/doi/full/10.1080/13658816.2024.2306167) - [THE CITY: Disadvantaged Communities flood funding (NY Climate Law)](https://www.thecity.nyc/2022/05/02/billions-ny-climate-law-disadvantaged-communities-flood/) - [Inman: Redfin First Street integration](https://www.inman.com/2021/02/18/redfin-starts-displaying-flood-risk-data-on-listings/) - [FACTUM: citation-hallucination detection in long-form RAG](https://arxiv.org/pdf/2601.05866) - [AMD x lablab.ai Developer Hackathon (May 4 to 10, 2026)](https://lablab.ai/ai-hackathons/amd-developer)