Mikhail Taver

Mikhail Taver is a career dealmaker turned venture investor with more than 20 years of experience across strategy consulting, M&A, and private equity. By his own account he has completed 250+ transactions totaling roughly $24 billion. Before venture capital, he was an executive at Nafta-Moskva — at the time one of Russia's most successful financial groups — and later at the AAR consortium (Alfa Group, Access Industries, and Renova Group), where he was involved in managing the consortium's 50% stake in TNK-BP, the joint venture between major Russian and UK oil companies. He holds the CFA, ACMA, and CGMA professional designations, reflecting a finance-heavy background unusual among early-stage AI investors.

In 2014, Taver co-founded Gagarin Capital Partners (with Nick Davidov), one of the first venture firms to specialize explicitly in artificial intelligence and machine learning — well before AI became a mainstream investment category. The firm became one of the most active AI investors of its era, backing companies that produced two headline exits to Big Tech: MSQRD (acquired by Facebook) and AIMatter (acquired by Google).

In 2020 the firm rebranded to Taver Capital Partners, and Taver now leads it as Founder and Managing Partner. The fund describes itself as investing in early-stage AI companies "from around the world, with a focus on the industrial sector." As of 2024 the firm reported roughly 20 AI startups backed and four successful exits, and was raising a second fund concentrated on Industrial AI. The team is supported by advisors including Kanishka Roy (CFO at SmartNews) and Mel Guymon (a former Yahoo and Google executive).

• Thesis: "A venture fund that invests in early stage artificial intelligence companies from around the world, with a focus on the industrial sector." Taver's conviction is that heavy industries — mining, manufacturing, energy — can be "given a second wind with the right AI tools," a segment most tech-focused VCs overlook.
• Stage: Early stage — pre-seed through Series A / A-plus.
• Sectors: AI applied to real-world problems; increasingly Industrial AI, alongside cybersecurity, health, fintech, agtech, legaltech, and computer vision.
• What makes him say yes: Founders who "demonstrate competence with concrete data," maintain solid financial models, work well as a complementary team (he cites family-only founding teams as a red flag), stay open to feedback, and think big-picture across disciplines.
• What he warns against: "AI for AI's sake." In his words, "AI is just a tool; there's no need to pursue AI for the sake of AI itself" — he wants AI deployed where it genuinely solves an industry problem.
• Realistic expectations: He openly notes Industrial AI is capital-intensive, takes ~5–6 years to validate, and produces non-linear returns — a deliberate contrast to fast-flip software investing.