Ventures

Sparticle Ventures Organizes Funds and SPVs supporting University Innovation

Sparticle Ventures mission is to organize investment vehicles focused on supporting innovation from leading universities. This includes student-led startups, alumni-led startups, and also research and intellectual property, where the outcome is ultimately commercial. We work with high net worth individuals, venture capital firms and corporate venture capital to identify high value opportunities early.

We split our funds into two groups: Venture Capital Funds; and Donor Funds. Both are focused on pre-seed and seed, with follow-on through Series A rounds.

ventures Venture Capital Funds and SPVs

Sparticle Ventures organizes early-stage venture funds that pursue long-term capital growth through investment into innovation and pre-seed/seed rounds of student, faculty or alumni-led startups or innovations. Funds invest only into startups that are commercial-ready. SPVs may invest into innovation research where licensing opportunities or a sale of IP is the targeted outcome. We use advanced A.I., natural language processing and machine learning to determine which startups and/or projects to pursue for investment. Carry from the funds and SPVs is shared with the university and also with evaluators who participate in the investment decision-making process.

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ventures Evergreen Donor Funds

Sparticle Ventures organizes evergreen donor funds that broadly support innovation, research and startups with a goal of making many, smaller investments to grow a universities innovation ecosystem and support bleeding edge projects having the most potential for exponential change. Donations to the fund are intended to be tax advantaged,* however we reserve up to 10% of the donation as an investment, so as to pass along the pro rata rights to donors in the fund. Pro rata rights in deals that go on to much higher valuations, and/or exits can be extremely valuable. Once again, in our evergreen donor funds we use advanced A.I., natural language processing and machine learning to determine which startups and/or projects to pursue for investment. Carry from the donor funds is majority shared with the university, so as to perpetuate the evergreen status, and also with evaluators who participate in the investment decision- making process.

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