One Concern’s mission is to create a category around benevolent intelligence whereby their technology is designed with a singular mission to save lives and economic livelihoods. OneConcern’s AI-based technology assigns a unique, verified “digital fingerprint” to every natural or manmade element from the smallest rock to complete structures to mega cities and eventually, the entire planet. They provide insights across the entire period—whether it’s days before a flood, minutes after an earthquake, or forward-looking policy and planning.
They aim to future-proof the world by combining human expertise, science, and machine learning to minimize the impact caused by natural disasters. Their data set also includes information on infrastructure and access to food, water, energy, shelter, and emergency services.
One Concern is a first-to-market planetary-scale resilience platform providing a single-point software solution that delivers real-time, actionable insights for decision-makers across public and private entities towards natural disasters. Their proprietary system helps optimize spend and resources towards preparation, response, recovery, and mitigation of natural disasters.
They work with governments, insurance, financial, logistics, and large private companies creating a global resilience network against natural disasters. The Company has built three hazard products addressing; a) seismic (earthquake), b) flood, and c) fire. Their technology is created to optimally predict the impact of natural disasters at the highest standard of accuracy.
One Concern is currently ramping up sales, having previously focused on building out theirproprietary single point, multi hazard technology. some text
● As of year end 2018, the Company reported a cumulative total contract value of $1.56million, with an ARR of $678,000.
● As of end of January, 2019, the Company reported further contract closings and a totalcontract value of $5.4 million, driven by the following:
○ SOMPO - $3 million for year 1 with an expansion in further years
○ American Family Insurance - $1.5 million
○ World Bank: $250k / year
○ Arizona - $250k/year **
○ SF - $100k / year
○ Existing Legacy Business (LA, Woodside, Cupertino, San Ramon) - $300k
One Concern uses four different data channels, which include:
1. Public data: USGS (US Geological Survey, US Census, US Dept of Energy andCommerce, LandSat and Tax Assessors Offices.
2) Privately purchased data: sensor data from buildings, satellite imagery, weather data, infrastructure and inventory data, social data streams.
3) One Concern collected and curated data: internal data collection and mining teams, developing machine learning on unstructured datasets.
4) Client’s proprietary data: individual customer data sets
They also include a multidimensional approach towards data input associated with ancillary variables such as:
- Soil
- Built environment
- Lot
- Satellite imagery
- Street view
- Social media
- Natural environment
- Socio-economic
- Demographic
- High resolution maps
One Concern trains all these disparate data sets to then create proprietary intelligence alongside understanding high resolution imaging for risk and vulnerability, managing manual imaging and computer vision techniques. By taking a “bottoms up” approach the Company is able to develop a dynamic AI powered model.
One Concern has three primary USPs:
1) Go-to-Market (GTM) - By focusing on the creation of resilience networks, with the city as the center of it, they have built a horizontal platform that unifies disparate silos of data and incentivizes users to work collaboratively. The more data that users contributes, the more accurate the prediction becomes. It also allows users to better understand shared resources and interdependencies and they can devise actionable strategies to minimize disruption. They are focused on partnering with cities to ensure accurate data access and in creating a revenue model monetizing private clients. Their stakeholders include:1) government; 2) insurance and banks; and 3) large private corporations.
2) Accuracy and Proprietary Algorithm - By developing multi sourced data system, including IoT sensing devices, they have developed a disaster prediction and management system with significantly higher accuracy at 85% accuracy v.s the status quo of 25-35% , within the first hour, for seismic predictions.
3) Reliability - Cities that are partnered with One Concern rely on their software, data, and scenario planning user interface as the Company fills in the “blind spots” associated with lack of data and information via their own team of data collectors and scientists.Supplementing with their own data layer allows to build a robust model, increasing accuracy and creating dependency from city customers, building a competitive moat.
The Company has built three hazard products addressing; a) seismic (earthquake), b) flood, and c) fire. Each hazard product has four modules - 1) mitigation, 2) preparedness, 3) response and 4) recovery with others in the pipeline associated with creating a metricize system for insurers.
PRODUCT A - SEISMIC CONCERN:
The Company reports that this product can predict impact of an earthquake on a block by block basis at an 85% accuracy, within the first hour. The product accounts for recent earthquakes, depth, location, historical trends, critical infrastructure of damage maps and buildings, and social equity analysis of at-risk population cohorts. This allows for realistic simulations to optimize planning and resource deployment. The product helps to decrease response time, prevent further damage, and optimize mitigative actions and live responses.
PRODUCT B - FLOOD CONCERN:
The Company reports this product is able to predict the level of water inundation outside of your homes and offices up to 5 days in advance of the storm occurrence. By mid-2019 the product will be able to predict riverine and coastal, urban and street flooding as well be used in response preparedness and mitigation. The product also monitors hydrological systems and downstream impact for jurisdictions alongside historical analysis to identify vulnerability trends.
PRODUCT C - FIRE CONCERN:
As a beta product, it utilizes data science and hazard modeling toward fire response. They combine satellite low-resolution data with remote sensing, fire-related and natural environment data to predict active fire boundaries, helping solve for the problem of identifying the origination of the fire. The product is able to identify and monitor active fire area and growth in real time for data driven decisions on evacuations and firefighter safety.
PRODUCT C - FIRE CONCERN:
As a beta product, it utilizes data science and hazard modeling toward fire response. They combine satellite low-resolution data with remote sensing, fire-related and natural environment data to predict active fire boundaries, helping solve for the problem of identifying the origination of the fire. The product is able to identify and monitor active fire area and growth in real time for data driven decisions on evacuations and firefighter safety.
Ahmad Wani, Co-Founder & CEO, is an environmental engineer. Earlier in his career, heperformed structural design and risk analysis for power plants for the Central Government ofIndia as an executive at NTPC, India's largest energy conglomerate. Ahmad holds a graduatedegree in Structural and Earthquake Engineering from Stanford University. He earned hisBachelor's of Science in Civil Engineering from the National Institute of Technology.
Nicole Hu, Co-Founder & CTO, is a computer scientist and AI engineer. Nicole holds agraduate degree from Stanford University in Computer Science and Machine Learning. Prior toStanford, she worked as a Software Development Engineer at Flipkart, the largest e-commerceplatform in India - Walmart acquired them for $16 billion. Nicole earned her Bachelors ofTechnology in Computer Science and Engineering at the Vellore Institute of Technology.
The founders were named Forbes 30 Under 30 top innovators in Enterprise Technology
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