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arXiv cs.AI
5/10

CivicReadiness

An AI reader that turns your county's disaster plan into a plain-language briefing, surfacing what's actually promised versus what gets cut — and who's left out.

Target user

Coastal and flood-prone residents trying to make sense of their local emergency plans before the next storm

Features
  • Plain-language briefing mode that translates dense policy into a two-minute read with plain definitions
  • Promise-vs-provision flag that highlights where stated commitments are quietly narrowed or unfunded
  • Who's-missing detector that flags when vulnerable groups (elderly, disabled, low-income, non-English-speaking) are not addressed
  • Side-by-side comparison of your county's plan versus neighboring jurisdictions so you can ask sharper questions at town halls
Why now

Disaster policies keep getting longer and more jargon-heavy; communities hit by repeated hurricanes, wildfires, and floods are demanding more accountability and a tool that does the jargon-deciphering for them.

Signals · overall 5/10
Demand
4/10

Searches surface FEMA/NOAA/state government preparedness pages rather than consumer apps; a Japanese factorial survey found only ~20% of flood-prone residents 'receptive' to disaster-app adoption while ~80% are 'unreceptive.'Who Pays for Preparedness? Valuing Disaster App Features Through a Factorial SurveyHurricanes - Get prepared - Canada.ca

Whitespace
7/10

No resident-facing app found that ingests a specific county's Emergency Operations Plan and translates it to plain language; existing offerings (FEMA app, NOAA, Emergency app on Google Play) focus on alerts and checklists, not plan parsing or gap analysis.Emergency Operations Plans / Emergency Management Program - ASPR TRACIE

Monetization
3/10

ResearchGate contingent-valuation work and the Japanese factorial study show low and seasonal willingness-to-pay for preparedness tools, and the Scribd 'Paths to Sustainable Civic Tech' report explicitly notes that few civic-tech startups achieve meaningful scale or sustainable revenue.Who Wants to Pay More? Exploring Citizen Willingness to Pay for Supporting Local Emergency ManagementPaths to Sustainable Civic Tech

Longevity
7/10

Climate-driven disaster frequency is rising and emergency plans are getting longer and more jargon-heavy; FEMA/NOAA preparedness infrastructure is permanent, and the policy-arXiv trend (discourse-aware policy analysis) indicates sustained academic and governmental interest.How AI Is Transforming Emergency Management in Canadian MunicipalitiesRevolutionizing emergency preparedness with on-demand mapping

Feasibility
6/10

LLM PDF summarization of EOPs is straightforward, but the 'who's left out' gap analysis requires argumentation/policy reasoning similar to the source arXiv framework; scraping and maintaining county plans at scale adds moderate data-pipeline work.Coastal Emergency Agent — EGU 2026 - GitHubAI and Community-Based Coastal Disaster Preparedness Strategies

Discourse-Aware Policy Analysis with Argumentation: A Hybrid LLM-Symbolic Framework for Disaster GovernancearXiv cs.AI · 2026-07-16 (9d ago)