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WAI To Go! ClimaCell Launches Historical Weather Data Archive For AI-Model Training That Can Predict Weather's Precise Impact On Businesses and Industries

BOSTON, Jan. 16, 2020 /PRNewswire/ -- ClimaCell, the weather technology company, announced today the launch of a new product, WAI - Weather for AI, a historical data archive for the training of AI models. With WAI, weather-sensitive industries and businesses can now easily access massive amounts of unique hyper-local historical weather data from every point on earth, and generate tailored AI-driven insights.

Decision makers will now be able to predict the specific impact of selected weather parameters on their operations, as well as gain a better understanding of the connection between weather and business performance.

Up until now, industries and businesses most vulnerable to weather have encountered two significant obstacles when trying to train their AI models based on historical weather data. First, they've had to rely exclusively on traditional tools of the weather trade such as satellites, radar and weather stations. These standard data sources produce vague results. Often times the data that's used isn't accurately calibrated to a desired location.  

Second, the data that's generated is frequently too massive and complex to be of any practical value. As a result, users can't customize this information to their specific business needs.

These two major issues have prevented businesses around the world from generating the actionable insights needed to stay one step ahead of Mother Nature, train their AI models, and better predict their future business outcomes.

ClimaCell's WAI is thus a game changer. Powered by a patented MicroWeather OS, ClimaCell applies AI and machine learning technology to its unique historical gridded weather data reanalysis to produce unparalleled accuracy. WAI's ultra-high resolution data sets date back years, and can be quickly and fully customized to train AI models by desired location, coverage, resolution, as well as specific weather and air quality parameters.

Customers can then use ClimaCell's MicroWeather API to use real time and forecast data that matches the resolution of WAI's archive.

This exclusive hyper-local historical data is derived from a global network of Weather of Things (WoT) virtual sensors – wireless signals, connected cars, airplanes, street cameras, drones, and other Internet of Things (IoT) devices. By fusing this data into cutting-edge AI-driven modeling techniques, WAI uniquely uses a hyper-local global grid of less than 500m to create the world's first data archive to provide ultra-accurate historical results for any location on earth.

"WAI's hyper-accuracy and unique historical reanalysis of gridded data will catalyze real time, data driven action. But beyond these game changing benefits users will be amazed by the seamless, intuitive way the service runs. Not only will using ClimaCell's historical datasets create tailored insights to predict business outcomes and drive better informed decision making, all this will be done in a fraction of the time that people today spend trying in vain to plan around the weather," commented Shimon Elkabetz, the CEO and Co-Founder of ClimaCell.

About ClimaCell

ClimaCell is powering actionable weather insights around the world. ClimaCell's mission is to help people and organizations manage their weather related challenges with the best information and insights.

Unique to the weather industry, ClimaCell fuses a proprietary big data collection and analysis platform with exclusive modelling techniques to create MicroWeather OS - an array of products that are providing clients hyper local weather data and invaluable business insights to create the world's leading weather intelligence engine for businesses.

ClimaCell's patented MicroWeather technology engine is powered by Weather of Things data - wireless signals, connected cars, airplanes, drones and IoT devices. This data is combined with proprietary AI-driven models to help people and industries to manage their weather-related challenges that impact everything from operational efficiency to profitability, safety and the bottom line.

https://www.climacell.co/historical-weather-data/

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SOURCE ClimaCell