Making film financing easier, fun and more predictable so that great stories get told.
Screencrib aims to increase the commercial success of independent feature films.
The Screencrib Model
Screencrib exists to empower independent creatives and audiences by giving them the collective opportunity to fund what they believe in. By turning the current development process on its head, we champion a new inclusive model whereby all members are given the collective opportunity to engage, build interest and nurture creative ambition, so that great stories get told.
Our Team
As CEO and Co-Founder of Screencrib, Ruby's lifelong commitment to the entertainment industry centres around the following mentality: Good stories, and the belief systems they communicate, are intrinsic to humankind and must be shared. It is this respect for film and its makers that fuels her dedication towards disrupting disconnected models of film financing to ensure that unique narratives reach their audiences. Having met James whilst executive producing a feature film in London, the pair instantly connected over their joint optimism for finding a simpler way to fund creativity. Now with much patience, enterprise and ambition they have developed Screencrib, which Ruby has made her primary focus and daily excitement.
As founder and CEO of Cognism, James draws affinity with entrepreneurial filmmakers who are dedicated to pursuing their dreams. A longtime proponent of the film industry, he decided in 2022 to personally invest into three independent feature films. During this process he gained first-hand experience of the challenges both talented filmmakers and investors face when engaging in the act of film financing. He has since developed a committed approach to solving this problem through his unique understanding of transparent technology. James approaches work with unrivalled technical and organisational skills, perseverance, precision and total dedication. He has significance experience in lead generation, sales management, and alpha discovery using algorithmic technologies, language processing, and machine learning.