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DeepBench
DeepBench is a platform that unlocks professional knowledge for enterprises. Its solution identifies expertise, and matches question-seekers with those who have answers. I sat down with Co-Founder and CEO, Yishi Zuo, (MIT MBA ’18) to hear about the platform and their plans for the future.
DeepBench’s Story

DeepBench’s platform began by attracting both 1) users seeking knowledge–the demand side, and 2) users sharing their expert knowledge–the supply side. They launched their marketplace by tapping into their networks to build robust demand from friends, connections and the MIT Sloan alumni network. They offered an easy trial for their clients, “Send us what you need and we’ll look for it.” The MIT Sloan network recognized their early value and made up much of their first roster of clients. The market for knowledge platforms is currently $76B with competitors such as GLG on the B2B side of the business and LinkedIn and Google for DeepBench’s SaaS opportunity.
“Send us what information you need and we’ll look for it.”
– Yishi Zuo, Co-Founder & CEO on their pretense for initial trial customers
Working through their clients’ requests, they started to build out the supply side of the platform. In the beginning, the DeepBench team were avid users of their own product. This allowed them to quickly iterate to optimize the user experience and build a supply network as they simultaneously met the demands of their initial clients. They attracted new and noteworthy clients including IDEO, which they connected with at MIT Fuse, and Deloitte, after meeting a fellow MIT Sloan alum in an Uber Pool.
The Product
Creating the initial marketplace enabled DeepBench to hone the functionality of their product. “Clients can use our platform to submit a project directly, look for experts, they can schedule things all on one integrated platform.” On the expert side, “We reach out to people, they automatically onboard, they can interact with clients directly.”
After they launched the marketplace, DeepBench garnered interest from organizations looking to license the platform for internal use via a SaaS model. A common problem in large organizations happens when a person in the organization needs to know something, but doesn’t know who can provide the best intel. “There’s certainly someone in the organization that knows it, but you have no idea who they are or where they are.” DeepBench enables companies to better connect knowledge internally as well as turn their workforce into expert consultants externally.
A new European regulation called MIFID II has created an interesting use case for DeepBench’s solution. The regulation pressured banks to itemize research fees, and as a result, their customers were demanding more customized and tailored research for the fees that they were paying. Macquarie, a $USD 30 billion market-cap global investment bank, looked to DeepBench to tap into its own employee network and provide the internal connections required to satisfy client demand. Macquarie derived such value from the platform that they decided to invest in DeepBench, becoming DeepBench’s first major investor. The early partnership with Macquarie has resulted in introductions to other organizations that would benefit from licensing their platform.
As such, the DeepBench team soon realized that there was a major untapped opportunity to not just operate a marketplace, but to actually license its software as a SaaS solution. This paved the path for a new phase of growth as other partners licensed the platform, creating an opportunity for future partnerships in a variety of industries.
Future Plans

The expert marketplace is already self-sustaining and cash-flow positive, with the added benefit of providing valuable UX feedback and generating customer leads for the software licensing model as well. DeepBench is expanding its SaaS offering and rapidly gaining new clients across sectors beyond investment banking, and they see it as de-risking the path to their long-term vision.
DeepBench’s ambitious mission unlock the world’s knowledge. They want to unlock the knowledge that not even Google can access, because much of it isn’t written down anywhere – the type of latent knowledge that is in each of our heads. Their vision is to become the go-to information platform for all knowledge workers. Yishi’s example is, “Imagine a world where you want to learn about bike helmets. You’d come to the DeepBench Platform, you’d type in bike helmets, and you might come across a few dozen pieces of user generated content, maybe a few blog articles on the manufacturing, distribution, or the marketing of bicycle helmets. Maybe there’s a video about cycling as an industry, another discussion forum about safety equipment. If you read something you like or see something interesting, you can just click a button to ask that person a question or schedule a call–all in one place.”
“If you think of something that is infinitely long-tail and has zero storage & shipping costs, it’s knowledge!”
– Yishi Zuo, Co-Founder & CEO
Unlike Quora or Reddit, DeepBench is focused on professional knowledge sharing amongst experts. It democratizes the social capital that a well-connected MBA or Venture Capitalist has, and saves the user time. In Yishi’s words, “When Jeff Bezos founded Amazon, he chose to sell books of all things because of its long-tail nature (millions of titles), and relatively low storage & shipping costs. Knowledge is a fascinating product for that same reason. If you think of something that is infinitely long-tail and has zero storage & shipping costs, it’s knowledge! So at the fundamental level, being a platform for knowledge is a great business model. As users learn about a topic, they’re going to want to talk to someone else to dive deeper. And given the nature of knowledge, one week you’re looking to learn about helmets, next week you’re looking to learn about water bottles, the week after that perhaps blockchain. As long as people remain curious, and the world becomes more complex, there’s infinite, growing demand for knowledge. That’s the amazing thing about the industry DeepBench sits in.