Venture CapitalRIA · CRD 336115SEC-RegisteredPrivate Fund Adviser

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eLab Ventures

eLab Ventures is managed by three equal partners: Paul Brown, Doug Neal, and Bob Stefanski, with offices in Ann Arbor, Michigan and San Mateo, California.

eLab Ventures logo

eLab Ventures

eLab Ventures is managed by three equal partners: Paul Brown, Doug Neal, and Bob Stefanski, with offices in Ann Arbor, Michigan and San Mateo, California. The firm publishes no founding year and does not disclose wealth origins. From the outset, it has concentrated on artificial intelligence as its single investment thesis. The firm targets early-stage, seed, and startup rounds, deploying into businesses where AI is the core driver of market disruption. It commits to direct equity positions rather than fund-of-funds structures, leaning on its dual-coast geography for deal flow. eLab’s website does not list portfolio companies by name, but its public-domain messaging and the “Impact Beyond Business” section confirm activity across AI-native verticals. The team sources from both established coastal startup ecosystems and underrepresented talent pools in the Midwest. Total capital deployed, fund sizes, and precise team headcount are not publicly disclosed. The partnership is supported by four advisors: Rada Mihalcea, Jon Oberheide, Mathew Johnson-Roberson, and Kunle Olukotun — each a technical figure in machine learning or systems research — alongside Associate Paul Stefanski. The firm runs a weekly “VC AI Report” newsletter, positioning itself as a thematic knowledge hub for allocators and founders tracking applied AI. eLab’s architecture is distinct in that it is fully thesis-bound: every investment criteria flows from the conviction that AI creates durable moats. The three managing directors sit as functional equals, a flat governance model closer to a tech partnership than a hierarchical fund. That structure gives the firm the ability to move at founder speed, unencumbered by institutional committee layers, while drawing on deep academic and operator networks through its advisor bench.

General information

Firm type

Venture Capital

Year founded

AUM

Undisclosed

Location

Region

North America

Country

United States

City

Ann Arbor

Corporate office

206 E Huron St., Suite 108, Ann Arbor, MI 48104

Additional offices

635 Mariners Island Ste 204, San Mateo, CA 94404

Principals

Paul Brown

Managing Director

Doug Neal

Managing Director

Bob Stefanski

Managing Director

Sector focus

AI/ML

Frequently asked questions

Who makes investment decisions at eLab Ventures?

The three managing directors — Paul Brown, Doug Neal, and Bob Stefanski — lead the firm. The website presents them as a flat, collegial partnership with no CIO or CEO designation. Associate Paul Stefanski and a roster of four technical advisors support sourcing and diligence.

What is eLab Ventures' investment thesis?

The firm invests only in companies where artificial intelligence is the primary source of competitive advantage. It does not diversify into non-AI verticals. This singular mandate drives its entire portfolio selection and differentiates it from generalist early-stage funds.

At what stage does eLab Ventures invest?

eLab targets early-stage rounds, including seed and startup phases. Its messaging emphasizes first-check capital, and the firm’s structure appears optimized for direct equity positions rather than later-stage or secondary market participation.

Where does eLab Ventures source its deals?

The firm operates from two offices — Ann Arbor, Michigan and San Mateo, California — and sources from both established coastal networks and underrepresented talent pools in the Midwest. Its advisor bench of prominent academic researchers provides additional university and lab-driven deal flow.

Does eLab Ventures disclose its AUM or fund sizes?

No. eLab does not publicly disclose assets under management, fund sizes, or total capital deployed. Its AUM therefore remains undisclosed, consistent with the practice of many early-stage venture firms that do not publicly share fund-level metrics.

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