One of our first investments out of Reach Capital was in a scrappy writing startup spun out of UC Berkeley, founded by English professor Don McQuade and his star student and TA Matthew Ramirez. They set out to solve their own problem: they were drowning in grading papers and didn't feel as if they were giving adequate feedback to their students. Yesterday, Chegg announced their acquisition of WriteLab, the AI-driven writing feedback platform. Grounded in a research-based pedagogy, WriteLab relies on machine learning algorithms to provide different categories of advice -- grammatical comments, logic, clarity and concision. WriteLab acts as a teacher's assistant, helping students polish their writing before turning it in.

WriteLab is a web application with a clear mission: to help you write better. Users upload or copy and paste their writing to the site, and WriteLab analyzes it using a combination of machine learning and natural language processing, then makes suggestions for how to improve the writing sample. WriteLab also comes with built-in analytics and document sharing capabilities, meaning it allows peer and teacher feedback to be integrated into its assessment. WriteLab is unique because it grounds its feedback in pedagogical principles. Instead of simply correcting a writer's mistakes, this web app makes suggestions and gives explanations for each so that the writer can understand the reasoning behind the corrections and decide which ones they want to keep. For instance, when I used the phrase "in recent years" in my writing sample, WriteLab asked, "What does in recent years add to your sentence?"

Matthew Ramirez was teaching writing classes to students at the University of California at Berkeley when he started to get frustrated. He was spending the majority of his time giving repetitive feedback to students, and there wasn't enough time to provide truly constructive, in-depth feedback to each individual before the next essay was due. "Given the time constraints of a semester and the number of students in a class, it wasn't humanly possible to respond to everything I wanted to," Ramirez said in an interview. "Nor was it possible to work through multiple drafts with individual students." Ramirez took it upon himself to build a solution.