Emergency: AI Disaster App for Homeowners

Emergencies are a Disaster for Communities:

There are $250B in annual uninsured disaster losses, with 86,000+ fatalities in 2023. Moreover in the US, 72% don’t understand Insurance Policies while 25% opt out of FEMA Alerts.

Emergency Tech is a Disaster for Everyone:

Climate adaptation innovations addressing ever growing disaster impacts are imperative and plausible, but not yet reality at necessary scales.

Emergency is "TurboTax for Disaster Recovery"

With our mobile App Homeowners video property damage, our AI Engine generates insurance claims, and submits reimbursements in minutes to their carrier & FEMA. This will save users $100,000’s from underinsurance, $10,000’s in reimbursements, and countless painful hours.

“Hurricane Wilma caused $100,000+ to our family home. My parents video’d our home before & after the storm, then hired a public adjuster to negotiate with State Farm. Over excruciating months they prepared our claim, interacted with the carrier, and maximized our claim.“ - Joe Russo (CEO)

Emergency App uses AI to do that in minutes - and in 10 years our Climate Intelligence Platform will seamlessly integrate citizen, insurer, and government risk data into an AI-driven climate adaptation experience saving lives and livelihoods.

Are initial customers are 215M insured homeowners in the United States.

We intend to scale to serve the Billions of homeowners across the globe.

We will use our AI Engine to validate insurance coverage, prepare claims in minutes, and maximize reimbursements, delivered faster with direct integrations to carriers.

This way we keep natural disasters from becoming economic disasters.

In 2021, Joe Russo (CEO) began full time on customer validation, attending Disaster & Emergency Management Conferences while mapping the industry’s tech ecosystem.

In 2022, James Olejar (CTO) joined, building a prototype web application finished just before Hurricane Ian’s landfall, earning media interviews from Fox News, CBC, Business Journals

In 2023, James Podlucky (CPO) joined, having been one of the first to prototype OpenAI RAG use cases for government agencies to protect communities in natural disasters.

Since January 2024, we’ve built strategic relationships to access 95% of all national insurance, weather, and government data to train our proprietary AI Engine.

Insurance data is accessible through our Canopy Connect partnership, with additional claims data accessible through LexisNexis (C.L.U.E. Database) who’s advised us on data architecture.

Last week we submitted a 3-year contract proposal to the Weather Channel, building the country’s first Emergency Notification database that also uses AI Zero-Shot Learning (ZSL) to categorize raw alert data and Natural Language Processing (NLP) to best communicate actions.

Emergency App is in prototype testing, ultimately adding a mix of visual Discriminative AI & generative AI to translate media into claims, along with Small Language Model (SLM) to efficiently guide users to input every data point that maximizes their claim.

Emergency can save lives and livelihoods of 100,000's annually - we believe it and know MIT SOLVE can get us their without a doubt.

Before | Mitigation & Preparedness Phases

UNSDG Indicator 11.5.1: Direct economic loss attributed to disasters in relation to global domestic product (GDP)

Key Question: Can we improve preparedness rates in at-risk communities, leading to the reduction of insured economic losses?

Ideal Outcome: 10% Reduction in insured disaster losses.

• Emergency Profile Score (EPS) | Survey basic preparedness based on total scores from FEMA National Risk Index and Canopy Insurance Data.

• Insurance Coverage | Track user’s applicable insurance, flood insurance, and parametric insurance for proper coverage.

During | Response Phase

UNSDG Indicator 11.5.2: Number of deaths, missing persons and directly affected persons attributed to disasters per 100,000 population

Key Question: Can we improve evacuation rates in impacted areas, removing more people from fatality equations and reducing deaths?

Ideal Outcome: 25% Reduction in indirect fatalities.

• Evacuations | Track real-time clearance time from notification to evacuation, while comparing to projections and past incidents.

• Shelter In Place | Survey individuals and families who are staying or leaving communities in the path of disaster.

• Notifications | Track the number of citizens informed during specific incidents, aligning to severity, timeframe, and engagements to their response.

After | Recovery Phase

UNSDG Indicator 11.5.3: Damage to critical infrastructure and number of disruptions to basic services, attributed to disasters

Key Question: Can we improve access to critical resources in the days and weeks after disaster, providing more equitable reimbursements and government funding especially to traditionally underserved populations?

Ideal Outcome: 25% Increase in claims & federal support reimbursements

• Incidents | Engage residents and governments in the post-incident disaster assessment, providing needed situational awareness to real-time task prioritization and FEMA grant reports.

• Feedback | Ask for feedback, including on behalf of government agencies to better plan for future deployments and disasters.

Losses | Provide insurance updates, gap insurance, and FEMA financial resources in a turbotax like format that tracks needs and engagements.

Our Emergency Platform leverages its users, unique data, and trained AI to build an end-to-end climate intel ecosystem:

• Emergency App | Mobile App with free & paid memberships accessing risk data with insurance offerings.

• Emergency Watch | Situational Awareness SaaS for public safety, insurers, media, and businesses.

LANGUAGES & FRAMEWORKS: Typescript, Node.js, AppSync/GraphQL, Python, React.js, React Native, MongoDB, Postgres, Redis, AWS w/ Serverless Microservices, OpenAI, Azure AI

PLATFORMS: AWS, ESRI, Github, Mapbox, Linear, Figma

James Olejar (CTO) oversees development, with 15 years of experience including the last 5 as head of innovation at the largest 911 Tech Startup in the US. James Podlucky (CPO) oversees roadmap, while running product at the largest public safety tech company in the US.

Joe Russo (CEO) has learned to code specifically to contribute and understand all aspects of technology capabilities. Jake Hinkle (Developer) is an Army Ranger and self-taught developer bringing additional subject matter expertise.

The team has strategized together for almost 2 years mostly online and sometimes in person. With natural disasters increasing, the pain for ordinary people growing, our public safety & innovation focused team is now ready to take the full time leap.

Joe Russo (CEO) & James Olejar (CTO) have known each other for 8 years through the tech community, hosting events and competing in hackathons. James Podlucky (CPO) has known the team for 2 years, meeting online through thought leadership exchanges and mutual passions to build technology for people in need.

Per our Pending B Corp Certification, we've adopted an Employee Handbook and Corporate DEI Policy to assure longterm adherence to a scalable company environment that allows our team to help communities, together.

We’ll charge a $100 ARR membership, with users able to pay later with their reimbursements.

Of 215M Insured US Homeowners making a $21.5B Total Addressable Market (TAM), 6% will submit natural disaster insurance claims, annually equating to a $1.3B Serviceable Available Market (SAM), while we’ll aim to initially capture at least 1% or $215M Serviceable Obtainable Market (SOM).

We’ve also identified B2B & B2G markets with at least $500M in TAM, but who’s partnerships provide innumerable growth and data value to the product.

While we intend to raise $MM in capital to scale product & growth, building a sustainable business model is paramount to our success.

Homeowner apps like Zillow (226 MAU) & Nextdoor (40 MAU) validate customers, yet public safety apps like Citizen App (10 MAU) & Red Cross (200K MAU) show a missed target exists.

Insurers like Allstate & StateFarm shared their desires for solutions with better UX than legacy carriers and their backend software can provide, with LexisNexis sharing dismay at inconsistent claims data - they are partners rather than competitors.

We see the most direct competitors in startups like FireBreak (B2B / Friends & Family) identifying potential risks with device photos & Dorothy (B2C / Third Sphere backed) providing immediate gap loans from insurance claims - yet these are siloed and AI agnostic.

By integrating insurance, weather, and government data, we offer a year-round homeowner app usable everyday while delivering a 100x ROI when it matters - no one does that.