Mark Velik

Partner, EVP
Mark Velik pairs a technical upbringing and banking and McKinsey experience with forecasting expertise, designing cash-burn and staged-hiring plans, viewing software like plumbing and closely watching founders post-investment.
How to contact Mark Velik
Stages their fund invests in
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Sectors their fund invests in
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Avg Check
$1M–$10M
N/A
Does their fund Lead?
No
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Geos their fund invests in
Mark Velik
Stages their fund invests in
N/A
Sectors their fund invests in
SaaS
AI
Enterprise
Fintech
HR Tech
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Avg Check
$1M–$10M
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Leads?
No
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About Mark Velik

Mark Velik’s path into venture is unusually technical for the field—he grew up talking database structures and programming logic with his computer-programmer mother, and before VC he sharpened his skills at three investment banks and McKinsey, building a reputation as someone especially good at forecasting and, more recently, at mapping out detailed cash-burn plans and staged hiring for companies trying to stay financially strong through slow markets. He also has a habit of looking at software the way you’d look at plumbing—asking what quietly holds a messy industry together—and he pays close attention to what he learns only after investing, like how founders handle stress and big decisions once he’s actually working with them on boards at companies such as CarClarity, CorePlan, and Modii.

About their Fund

Sectors
SaaS, AI, Enterprise, Fintech, HR Tech
Rounds
Series A
Avg Check Size
$1M–$10M

EVP is known for high founder affinity, ranking #2 in Astral Ventures' anonymous VC Leaderboard among ANZ funds and ahead of many larger names, and for being a low-profile, relationship-driven firm led by Howard Leibman, known as the founder whisperer, who takes an active, hands-on approach by sitting on boards like Practice Ignition and Deputy and building concentrated portfolios rather than spreading bets across many companies. The fund now focuses specifically on early-stage AI-first software companies building for global scale, backing serious software businesses at the Series A stage using criteria like economic quality, earned founder market fit, and compounding advantage, while also offering structured support such as executive hiring through resources like Talent_OS.

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