Full stack content creation through artificial intelligence

We use the latest machine learning techniques to transform raw data into quality content for end users.

The process requires the three steps of creating databases, building models to analyse that data and creating natural language systems to pass on the analysis to the readers.

Creating Databases

Every project starts with us working out what data we will need for the content project, obtaining that data and building efficient databases to store and extract it from.

Data Analytics

We use neural networks and reinforcement learning to extract knowledge from raw data. This includes creating predictive models and discovering what information the end users need to know.

Explanations by NLG

The final part of our pipeline is to convert our analytics into natural language to provide content for human readers. These explanations can be supplemented with automated charts and graphics for use on websites and social media.

Frog The Gambler

Our inaugural platform is FrogTheGambler.com. The platform generates over 4,000,000 words of unique content each week. FROG.AI writes previews, draws and describes key statistics, and looks for positive expected value betting predictions on up to 2,000 global football matches in a single day, while also promoting a socially responsible gambling message.

Total Words

245,207,477

Total Articles

342,934

Days Since Launch

539

The FROG.AI API can provide content for long Natural Language Generated articles, short form NLG comments, social media comments and graphics as well as charts.

CEO and Co-Founder; David Hipkin studied Psychology and Applied Statistics before embarking on a career that took him from the city, via online sports journalism, in to product development in sports betting and trading. He is responsible for commercialising FROG.AI’s proprietary natural language generation technology.
CTO and Co-Founder; Chris Fawcett was a professional gambler for over a decade before obtaining a Masters in Intelligent and Adaptive Systems at Sussex University. Chris specialises in building our prediction models and overseeing our platform development. His areas of expertise are data manipulation, deep neural networks and reinforcement learning.

Contact Us

Please email us if you have any questions about our proprietary technology and how we may be able to help you create scalable automated content.

email : chris@frog.ai