Starting in 2014, Tanu has been working on this model, the science and the technologies surrounding it for about 3 years now. Our first major paper (http://credcount.com/whitepaper) was reviewed and published in late 2014 in a top CS conference. Although the majority of the work such as data collection was finished in approximately 8 or so months, there are certain analyses that have taken place up until today. That said, we are in what we consider the prototyping stage: the service/technology in its current form is not suited to any specific market but rather a proof of concept. With a little bit of modification to the machine learning models, we feel as though we can target new markets in as little as a couple weeks. Thus, Christian has spent the last few months trying to identify where we fit and have the biggest effect as a company/product. So far, we’ve considered news, politics, finance and the public sector. With contacts such as news anchor George Howell from CNN, political advisor and campaign manager Jason Boles and Senior Vice President of investments Mr. Jeff Wolk from Raymond James in the financial sector, we feel as though our best fit at this moment is to ride the “fake news” wave. Currently there is no window dressing to our model. In its current form, it is command-line driven (literally “python model.py [input]”), but we feel as though who our potential customers might be should be identified before we begin to work on any sort of graphical interface and/or API. That’s why we’ve come to YC. Our idea currently is a product/application built around our technology as an easy to use display of current news items and their credibility rankings such that someone might be able to read through an article with a presumed level of bias or accuracy up front. It comes through the narrative of “news literacy” and an attempt to have all sides of every story. Think if every fact or bullet from a news article could have a certain score for credibility such that the least items with the least standing fall to the way side and only the true and solid facts of the situation are left. How long have each of you been working on this? Have you been part-time or full-time? Please explain. Tanu has been working on CredCount since early 2014 as part of her PhD in social computing with her advisor Eric Gilbert at Georgia Tech. The majority of data collection and analysis led into early 2015, and she’s continued to circle back to it in a “part-time” role as a project with the most potential as a product/service outside of academia. Christian joined on early this year, 2017, in a product manager capacity to build this paper/model into a business. Working part-time while taking classes since his joining, he’s found himself devoting more time towards this venture than schoolwork, such that Tanu and Christian both are ready to commit to the project for the summer and however long after that.