MIT delta v is an accelerator for entrepreneurial teams at MIT. At least that's what the website says, because the program might be better described as a pressure cooker for entrepreneurs.


Based out of the Martin Trust Center, an experienced team of mentors provides hands-off guidance throughout the summer. Mentorship praxis is designed to allow for organic growth for both the individual entrepreneur and their team; it resembles Yoda training Luke how to think rather than a teacher instructing students how to color inside the lines. From June through early September, teams are tasked with answering fundamental questions about their business: Who are your customers, what are your customers' problems, and how exactly will your product solve these problems?


As MIT engineers, it’s easy to answer questions and solve problems, but delta v assumes an entirely different tack. Teams are given the freedom to ask their own questions to find new problems. You're never handed answers nor shown problems to solve, and it's with this Jedi-Training that the delta v magic takes hold. Soon teams begin seeking better questions, instead of quick answers, and with better questions comes insight into real problems worth solving.

The right question is worth a thousand answers.


Now, that's not to say you're left alone to question the world. Industry experts, mentors, and fellow entrepreneurs meet with you during the program to establish milestones that keep you honest in your quest for the right questions. This community comes from the broader MIT and Boston entrepreneurial ecosystem and is chosen within the ‘orbit’ of your team's broader industry (i.e. healthcare) to help support the high likelihood that your team could pivot, as we did. Additionally, your performance and interaction with mentors is evaluated to advise your team's performance.

The 2018 delta v cohort.

The summer was a time for our team to finally come together outside of work, classes and part-time schedules. Inclusion of team building sessions during the summer were an unexpected boon for our cofounder bonding. These sessions were led by Peter Senge, a world-leading expert in organization learning from MIT Sloan. Similar to the problem-solution journey, Peter’s lessons guided teams to identify and collectively solve the interpersonal challenges that were unique to each team.


Our venture officially launched on Demo Day as each team delivered their pitch in front of thousands of investors, students, and the broader MIT community. In our case, CEO Ryan Davis took to the stage to introduce the problem of data accessibility in healthcare and our solution using secure computation middleware. While entrepreneurs are fortunate to receive the growth-experience of delivering a solo pitch, the process requires an entire team’s unwavering belief and support. The pitch is the rarest and most cherished skill that a founder can learn to deliver:

The delta v program can be as punishing and as rewarding as one wants. We wrestled with finding our product-market fit and with concisely articulating our highly technical solution. Being founded by an amazing engineering team from MIT, we first communicated our enthusiasm for our breakthrough technology, instead of highlighting the problems we could solve for customers. Technical jargon like "federated learning" and "secure computation" made perfect sense to us, and so we learned from mistakenly communicating the same way to non-technical customers.


Fortunately, we improved our communication with customers as we applied delta v philosophy of asking better questions of our company and our customers. Does healthcare data need to be removed from silos? With the encryption security provided by our tech, who would benefit from accessing siloed data? How do we explain that algorithms can travel to siloed data by leveraging existing security infrastructure? These are only a handful of the questions that we have been able to ask our customers since exiting MIT as we begin to deploy our data silo middleware to help data scientists quickly and safely analyze information trapped inside healthcare data silos.