DryPowder — VC Intelligence for Founders

7 Seed AI & Machine Learning Investors in New York — 7 Currently Deploying

Updated

7
Total funds
7
Currently deploying
100%
Deployment rate
$250K–$25M
Typical check range

Funds (7)

Aspira Capital Management
● Deploying $250K–$2M

Empowering historically excluded founders with capital, mentorship, and networks to build scalable companies in Fintech, SaaS, AI, Logistics, and Healthcare, leveraging 25+ years o…

Point72 Ventures
● Deploying $500K–$10M

Thematic-driven investors backing ambitious founders building for big outcomes across critical domains (AI, Consumer, Defense Tech) from seed to pre-IPO, bringing deep sector insig…

Lux Capital
● Deploying $500K–$25M

Turn sci-fi into sci-fact by championing companies at the intersection of the new and not-yet-imagined, looking decades into the future to create a world most can barely imagine.

Charge Ventures
● Deploying $250K–$750K

Partner with exceptional founders at the very inception of their entrepreneurial journey, focusing on pre-seed and seed stage investments with a data-driven approach across non-tra…

Oceans
● Deploying

We help founders at seed stage with what matters most: building world-class teams, go-to-market strategy, and fundraising guidance, drawing from firsthand operational experience of…

Betaworks
● Deploying

Investing, building and working with exceptional creators and makers since 2008. Focus on AI agents and developer tools as evidenced by AI Camp and agent-focused events.

Union Square Ventures
● Deploying

Invest at the edge of large markets being transformed by technological and societal pressures.

Which of these Seed AI & Machine Learning funds actually fits your startup?

DryPowder's AI matching ranks all 7 by thesis fit, check size, and deployment status.

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Related investor lists

Pre-Seed AI & Machine Learning →Series A AI & Machine Learning →Series B AI & Machine Learning →Series C AI & Machine Learning →Growth AI & Machine Learning →
Seed Fintech →Seed SaaS →Seed Healthcare →Seed Consumer →Seed Biotech →Seed Crypto & Web3 →

Frequently asked questions

How many seed ai & machine learning investors are actively deploying right now?

DryPowder tracks 7 seed ai & machine learning funds. Of these, 7 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 seed ai & machine learning VCs write?

Among 7 seed ai & machine learning funds on DryPowder, check sizes run from $250K–$25M. 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 seed ai & machine learning VC?

A warm intro is still the fastest path. Most seed 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 long does a seed round typically take to close?

Seed rounds typically take 3-6 months from first meeting to close. Most of that time is spent on qualification: investors want to see early traction, run multiple meetings, and often complete reference checks. With a committed lead who sets terms, the rest of the round usually fills within 2-4 weeks. Without a lead, the process drags. DryPowder's deployment signals help identify which seed funds are actively writing checks right now versus sitting between vehicles.

How many seed 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 7 seed 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 7 seed 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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