The Michigan Venture Capital Association is proud to offer the Venture Fellows Program to Michigan’s venture capital community. The program, launched in 2023, is designed to increase the number of venture professionals in Michigan in order to accelerate the fundraising and deployment of capital into early-stage companies.
About Alex
Alex Motey brings a distinct blend of entrepreneurial execution and rigorous financial analysis to Augment Ventures. As a cleantech founder and strategic finance operator, he excels at navigating the intersection of technical risk and commercial scalability for early-stage ventures in foundational industries. His perspective as an investor starts with building. As Co-founder and CEO of Nataqua, a modular electrochemical conversion venture, Alex led a cross-functional team from zero to one. Having built inside a foundational industry, Alex evaluates the deep tech and software reshaping those sectors from the operator’s side of the table, judging not just the technology but whether it fits how the industry actually buys, works, and scales. Before his operating roles, Alex was an Investment Analyst at Parabellum Acquisition Corporation, where he sourced industrial-IoT targets. Earlier, he held Senior Financial Analyst roles in corporate finance. Alex is an MBA candidate at the University of Michigan’s Ross School of Business and holds a Bachelor of Science in Finance from Tulane University, where he served as an Equity Research Analyst, and published fundamental research on global telecommunications.
What are you most looking forward to about being a Venture Fellow?
This fellowship is paramount to continuing to my growth at Augment Ventures. I am extremely grateful for this fellowship. I am most excited about the networking opportunities, immersing myself more with the Michigan entrepreneurial community, and growing my career in venture capital.
What attracts you to Michigan’s venture capital industry?
Michigan is experiencing a revitalized, renaissance moment in its history. So, the environment in Michigan right now is ripe for early-stage opportunities. A great example is NOX Metals, which I can see continuing to thrive in our current industrial revolution.
What ideas do you have to support and advance DEI in our entrepreneurial and investment community?
A couple of facts to set the stage: roughly 25% of all US seed and pre-seed dollars go to startups with at least one founder from Stanford, Harvard, or MIT (Crunchbase, 2026), and the 10 leading VC firms put 51% of 843 seed checks into top-10-school founders (Beta Boom, 2024). A randomized field experiment shows investors respond to founder pedigree with the actual company held constant (Bernstein, Korteweg & Laws, Journal of Finance, 2017), and a study of 16,054 accelerator companies found up to half of follow-on decisions were “predictably bad” due to over-indexing on founder background (Davenport, University of Chicago, 2022). So, my conclusion is that venture capital’s biggest allocation error is treating pedigree as a proxy for ability. The failure rate is brutal for everyone; what differs is that capital chases a credential that moves investor demand even when the company is identical, and that over-indexing measurably costs returns. I saw this firsthand with CO2 conversion companies, and it’s a lesson that guides me today: I put no weight on pedigree. I care about: what a team is building, why, and what they’ve already done to prove they can execute.
What do you hope to be doing in 10 years?
I would like to have a profound impact through technology entrepreneurship, both as a venture capitalist and entrepreneur. Life changes, but I hope to maintain these goals as I grow.
What’s your dream deal — the company you wish YOU had spotted first?
I’ll flip this question and share my recent finding. While running technical due diligence on an enterprise AI company we’re currently investing in, I quantified something the consensus is missing. The buildout’s own financers expect corporations to shoulder the bulk of the roughly $5 trillion AI infrastructure program, which needs about $650 billion a year of revenue just to earn a 10 percent return (JPMorgan, 2026). Yet enterprises’ direct spending on frontier AI models is only $23.4 billion this year, about 3 percent of the $788 billion going into data centers in 2026 alone (Gartner, 2026). By my internal analysis, 60 to 75 percent of the expected enterprise consumption never shows up, and the reason is architectural: the systems that actually win enterprise automation make small, scoped model calls and accumulate the intelligence in a customer-owned learned layer, so they consume one to two orders of magnitude fewer tokens per dollar of business value than the forecasts assume. Frontier LLMs (OpenAI, Anthropic, etc.) become commodity inputs, and the value accumulates in the learned-model layer, which is exactly the layer Across occupies. This should start to solidify in July of 2028, and become clear in July 2029.