Machine Learning-Enabled Sales Research Assistant, Zymewire, Among Latest Cohort to Graduate Toronto’s Creative Destruction Lab
Currently supporting contract service companies in pharma/biotech, the Canadian startup looks to quickly accelerate growth and expand team size
Zymewire, a SaaS company developing machine learning-based solutions for commercial teams, announced their graduation from the 2017/2018 Artificial Intelligence stream of the Creative Destruction Lab (CDL) program at the University of Toronto’s Rotman School of Management. Zymewire uses deep learning to create insights about any company, identifying what they have done in the past, what they are doing now, and what they intend to do in the future. Their first application is a digital sales research assistant that helps business development teams uncover new opportunities for sales growth by combining this deep market intelligence with existing internal data.
After being selected for the program from over 600 applicant companies in September 2017, Zymewire is among 60 ventures in the latest cohort to graduate. “There is no question we emerged as a different company than when we started 8 months prior. Through the CDL network and the advice we received throughout the program, we now have a clear path to our next major revenue inflection point and clarity around what our company will look like as we add the next 85 team members” said Pete Bastedo, Zymewire’s CEO & Co-Founder. “The depth of expertise and raw intelligence in the room at CDL is just humbling: everyone from leading academic luminaries of AI through to entrepreneurs who have built billion dollar companies from the ground up. CDL gave us the chance to to sit down with dozens of incredible thought leaders and get insight and advice into how to move Zymewire forward in every way.” said Ryan Drake-Stoker, Zymewire’s CTO & Co-Founder.
After completing CDL, Zymewire now has their sights set on adding members to their team and expanding upon the success that they have achieved. “We have big plans in the future across many more industries and verticals where we see applications of our machine learning-based technologies!”