Barrow Green, LLC | Founding a Deep Tech Startup

Team: Lawrence London, School of Law J.D./L.L.M. ’89

About the Venture: BarrowGreen is pioneering a compact, lightweight, and energy-efficient cooling and heating technology that eliminates hydrofluorocarbons (HFCs). Designed for both large and small-scale applications, its first product—a cooling vest—aims to protect workers from extreme heat while minimizing environmental impact.

I am a cofounder of Barrow Green, a startup developing a compact, lightweight, energy-efficient cooling and heating technology which doesn’t use greenhouse gases. Barrow Green is considered a “deep tech” startup because it is developing an early-stage technology that has not yet been fully proven technically or commercially.


Barrow Green is not my first deep tech startup. I previously cofounded a computer hardware startup seeking to develop storage area network technology to reduce latency and increase input/output speeds by orders of magnitude. I have also been involved as a mentor or advisor in several deep tech startups. My computer hardware startup didn’t get off the ground because, although we were able to attract interest, we were not able to raise the funding that we needed to develop the technology.


I joke that I am attracted to deep tech startups because of masochism. The real reason is that deep tech startups have the chance to make a difference and to become wildly successful. However, there are many obstacles along the way.
At the other end of the spectrum, I once joined a startup that was seeking to put small businesses on the cloud. The business, which was selling an established service, had no unique strengths or advantages. Not surprisingly, the business went nowhere.


I believe that the sweet spot for a startup lies somewhere in the middle between deep tech on the one hand and ubiquitous technology on the other.


The challenges with launching a deep tech startup include the following:

  1. It is Hard to Raise Private Capital: Investors (including strategic investors) are often skeptical whether new technologies will work and typically, at a minimum, want to see a working protype before investing. The catch 22 is that funding is required to build the working prototype. Investors are much more hesitant to invest in hardware development than software development because of the perception that hardware is riskier and requires more capital.

  2. It is Hard to Get Government Grants: I have seen from my own experience, as well as the experience of other entrepreneurs, that getting government grants is tough. Government grants are intended to fund the development of innovative technology that is too risky and too early to be funded by the private sector. However, the government is also risk averse and government officials don’t want to be second guessed for unsuccessful projects. As a result, any perceived weaknesses in a proposal (e.g., the commercialization plan) can be fatal. Barrow Green currently has an Army Phase II SBIR award and, in addition, is part of a team on a NASA funded project. We have several pending grant proposals and are optimistic that we will be successful on at least some of these proposals. The reason for our optimism is that we are now in a position where our past performance, technical team, teaming partners, letters of support, and proposal writing team are all strong. Success begets success. One mistake that I made with my computer hardware startup was in rushing an application for a NSF Phase I SBIR. We applied without having obtained strong letters of support. We would have been in a better position if we had waited until the next cycle when we would have been more prepared.

  3. It Takes a Long Time: It can take a deep tech startup 5 – 10 years to develop its first product and to start generating revenues. Launching a deep tech startup is a marathon, not a sprint.

  4. Nobody Knows What it Will Take: I’ve looked at licensing technologies from various federal and university laboratories. When I ask for an estimate of how much money would be required to develop these technologies, I’m often given an estimate of $1 million, a nice round number that sounds difficult to raise but not impossible. The truth is that nobody can accurately estimate how much it would cost to develop early-stage technologies.

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