How did Runway achieve initial product-market fit and what are the current measurable milestones in that regard?

Runway started as a research and experiment-centric company. Our first product was a machine learning model directory, an app store of ML models, where you could play with hundreds of machine learning models. We started here because we knew that there was a fundamental shift happening around a nascent technology that needed to be experimented with and tested. Deep learning and computer vision techniques are forever changing the creative landscape and the media ecosystem. In other words, ML is transforming how we think about images, how we create video, and how we understand creativity. We needed the space to incubate its impact.

As the model directory and user base kept growing, we started seeing interesting usage patterns. One common thread was video. Video editors and filmmakers were coming to Runway because they saw huge potential in leveraging models to help them reduce the burden of the repetitive and manual aspects of video editing. Some estimates say that around 80% of the time spent on video editing involves uncreative operations such as tedious frame-by-frame editing. And so, a regular request we started to get was around workflow optimizations: "Hey guys I saw you have a model to do X can you also do Y and Z? I hate having to do this by hand.”. This pattern began with object segmentation models, a process known as rotoscoping in the video domain, and then expanded to things like context-aware infilling (video inpainting), video depth estimation, transcription, background noise removal, and audio generation among many other things. We tapped into that potential, spent time understanding that vertical, and went full into transforming the video editing process. Automating all the time-consuming, expensive, and hard parts of video editing using machine intelligence. The goal is to leave time to the core creative process of telling a story, whatever that story is. It doesn’t matter if it’s an ad, a product demo, a tutorial, or a webinar. 

As we started to build the first prototypes of this new approach to video editing using all the learning from the model directory phase, we quickly realized the more expansive impact of this approach. By simplifying the editing process, besides cutting the time and cost of making video, we are democratizing video editing and filmmaking at large, opening the door to a whole new generation of creators to use software in a more intuitive, collaborative, and powerful way.