5 Growth AI & Machine Learning Investors in San Francisco — 5 Currently Deploying
Updated
Funds (5)
Kleiner Perkins partners with visionary founders to build transformative companies that change how the world works. The fund emphasizes team building, network facilitation, and bus…
Bold, early, impactful ventures with brutal honesty. Believe in world-class teams making contrarian bets on impossibly big ideas, from AI to cleantech to deep tech.
Back exceptional companies with substance and soul, converting momentum into market dominance through five decades of experience and institutional support.
Providing resources and counsel to forward-thinking companies revolutionizing how we live, work, and play, with favorable terms and less dilution than traditional VC models.
Partner with entrepreneurs from early days through every stage of growth, focusing on transformative technology across AI/ML, biotech, cloud, consumer, and crypto sectors.
Which of these Growth AI & Machine Learning funds actually fits your startup?
DryPowder's AI matching ranks all 5 by thesis fit, check size, and deployment status.
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Frequently asked questions
How many growth ai & machine learning investors are actively deploying right now?
DryPowder tracks 5 growth ai & machine learning funds. Of these, 5 are currently deploying capital based on recent fund closes, portfolio activity, and partner signals. Use DryPowder's fund matching to see which ones fit your specific startup.
What check size do growth ai & machine learning VCs write?
Among 5 growth ai & machine learning funds on DryPowder, check sizes run from $500K–$50M. Ranges vary by fund size, vintage, and whether the fund leads rounds. Each fund profile shows check size detail and lead preference.
How do I get a meeting with a growth ai & machine learning VC?
A warm intro is still the fastest path. Most growth ai & machine learning VCs on DryPowder do accept cold outreach or direct applications, but response rates vary widely by fund. Before reaching out, use DryPowder's AI matching to get a fit score and specific talking points. Founders who lead with thesis-aligned framing get significantly better response rates than those sending the same deck to every fund on a list.
How is growth-stage fundraising different from earlier venture rounds?
Growth-stage processes resemble private equity diligence more than typical venture fundraising. Expect 4-8 months, financial audits, customer reference programs, and engagement at the CFO and board level. Most growth funds require 6-12 months of auditable financials and focus on financial performance, competitive moats, and management team depth rather than founder narrative.
How many growth ai & machine learning investors should I be talking to at once?
Most fundraisers recommend a parallel process: identify 20-40 target investors but approach your highest-fit funds first. Of the 5 growth ai & machine learning funds currently deploying, not all will match your specific stage and sector. Use fund matching to find your top 10-15, approach those first, collect feedback, then go wider. Going to every fund simultaneously without qualifying first burns bridges and dilutes the urgency that helps close a round.
How is DryPowder different from building a VC list on LinkedIn or Crunchbase?
The fund list you build on LinkedIn or Crunchbase is roughly the same list every other founder is building. DryPowder adds three things a manual search cannot: deployment signals (which funds have recently closed new vehicles and are actively writing checks), AI thesis matching (which of the 5 growth ai & machine learning funds actually fits your specific startup, ranked by fit), and verified partner contact details. The goal is 15 targeted, thesis-aligned pitches instead of 150 generic ones.
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