Underdog Labs

Underdog Labs Research Investment Thesis Underdog Labs is a pre-seed venture capital firm focused on backing belief-driven founders at the very earliest stages of company formation. Founded by serial entrepreneurs David Hehman and Alex Chang—who co-founded GetawayZone in 1997 and sold it to Expedia in 2000—the firm embodies a philosophy of shoulder-to-shoulder collaboration with founders. They believe the best companies are built by mission-driven teams with a clear understanding of their first "winnable chapter." Rather than imposing a narrow playbook, they adapt their approach to each founder's unique situation, combining capital with hands-on operational support to help de-risk and accelerate early-stage ventures. Stage & Check Size Underdog Labs specializes exclusively in pre-seed and seed-stage investments: Pre-seed : Typically pre-product or pre-monetization rounds of $500K-$1M Seed : Early revenue companies in rounds of $1M or less Check size range : $5K-$500K per company Positioning : Often the first institutional investor for portfolio companies Investment approach : Hands-on support with founders, de-risking operations before scaling Investment Criteria Underdog Labs is highly selective with four core criteria: 1. Mission-Driven Founders : They seek founding teams motivated by a true long-term mission with a clear, achievable first chapter. Belief in the founder's vision is paramount—they back people as much as ideas. 2. Early-Stage Focus : They invest very early, typically in rounds of $1M or less, often before product-market fit or revenue. This allows them to be present during the most critical de-risking phase. 3. Distribution Channel Understanding : They tend to invest in sectors where they or their network understand the distribution channels. Primary focus areas include B2B software and consumer products where channels are well-understood. 4. Avoidance of Hardware/Regulatory : They explicitly avoid businesses requiring significant hardware manufacturing or regulatory approval, as these create unpredictable timelines and capital requirements beyond their model. Portfolio & Recent Activity Underdog Labs has deployed over 100 investments across two funds. Fund II ($250M+) is actively deploying with significant recent wins: Recent Portfolio Milestones (2025): Code Metal (Seed → Series A): $36M Series A led by Accel for AI code generation at the edge Tennr (Early backer): $101M Series C at $605M valuation (healthcare referral automation) FloVision Solutions : $8.7M Series A for AI-powered food production analytics Arbital Health : $31M Series B for value-based care risk management Blue Onion : $10M Series A for financial data infrastructure Oscar AI : December 2025 investment in QSR franchise AI solutions Synaptrix Labs : Non-invasive brain-computer interface (BCI) platform backed by Mark Cuban Keebler Health : $6M funding for value-based care optimization Obviant : $7.1M Series A for defense acquisition data platform Portfolio Composition : 100+ companies across diverse sectors with demonstrated exits and significant follow-on success. Notable exit: GetawayZone merger/sale to Expedia (Hehman & Chang's founding company). Current Focus Areas (Based on 2025 portfolio): B2B AI (development tools, enterprise automation, healthcare AI) Vertical SaaS solutions Healthcare innovation (value-based care, referral automation, healthcare AI) Financial technology and data infrastructure Food/Climate tech Advanced technology (BCI, defense tech) Team & Investors General Partners: David Hehman : Co-founder with 25+ year entrepreneurial track record. Founded GetawayZone with Alex Chang; sold to Expedia in 2000. Multiple successful ventures since. Alex Chang : Co-founder with matching 25+ year relationship with Hehman. Deep startup experience and demonstrated success in building and scaling companies. Investment Team: Matthew Larson, CFA : Associate with deep experience evaluating consumer and technology businesses. Works with Howard Love's family office on capital allocation across public/private markets. Paul Borowick : Berkeley Haas MBA (class 2025). Started career in medtech as engineer and BD. High deal-sourcing energy. Howard Love : Advisor and significant LP. 25+ years investing in 150+ companies and 40+ PE/VC funds. Notable early backer of Trulia, HotelTonight, iSpot.TV, FlexJobs. Philosophy : The firm emphasizes the 25-year co-founding relationship between Hehman and Chang as foundational—proven trust and shared entrepreneurial experience are central to their value proposition. Decision Process & Involvement Decision Making : Partnership approach. Both GPs evaluate opportunities and work collaboratively on portfolio support. Advisory board members (Love, etc.) provide strategic input on capital allocation. Timeline : Conservative timeline (~1-3 months typical), given the relationship-driven, hands-on approach. They move quickly on founder fit but thoroughly evaluate market opportunity. Board Participation : Hands-on involvement without formal board seats. GPs and advisors actively support founders on de-risking, hiring, fundraising, and strategy. Follow-on Investment : Maintain reserves for follow-on participation in subsequent rounds for portfolio companies (observed in multiple Series A follow-ons). Geographic Focus Primarily United States , with strongest presence in: San Francisco Bay Area (headquarters) New York Secondary: Selective investment nationwide based on founder quality Co-Investors & Network Frequent co-investors and partnership alignment: Y Combinator Basis Set Ventures First Round Capital a16z, Lightspeed, Foundation Capital Accel IVP Various angel investors and family offices Sector & Model Preferences Primary Sectors: Enterprise Software / B2B SaaS (vertical SaaS, workflow automation, analytics) Healthcare Technology (value-based care, referral automation, healthcare AI) Developer Tools & AI Infrastructure (code generation, edge computing) Financial Technology (accounting, financial data, tax automation) Food/Climate Technology (yield optimization, sustainability) Advanced Technology (BCI, defense tech) Technology Tags: AI/ML (heavy focus across portfolio) Healthcare Tech Enterprise automation Founder Preferences: Belief-driven with clear long-term mission Experience in their domain or related fields Ability to articulate a "winnable chapter 1" Collaborative, coachable mindset (they explicitly work "shoulder to shoulder") Preferred: Founders with some initial validation or clear distribution understanding Notable Characteristics Accelerator-Style Support : Hehman and Chang explicitly position themselves as providing "boutique accelerator-style support," not just capital. They leverage their 25-year relationship and entrepreneurial playbook to de-risk early-stage ventures. Sourcing Method : Primary sourcing through trusted referrals. They favor warm introductions and founder networks over cold outreach. Deal flow from portfolio founder recommendations is core. Success Metrics : Demonstrate belief-driven investing that has produced multiple unicorns (Tennr at $605M post-Series C, multiple $100M+ exits), with sustained portfolio success over 100+ investments. Fund Status : Fund II actively deploying as of December 2025. No public information on Fund III yet, but based on portfolio velocity, clearly in growth mode. Anti-Profile Underdog Labs explicitly does NOT invest in: Businesses requiring significant hardware manufacturing Companies dependent on regulatory approval (extended timelines) Opportunities outside their distribution channel expertise Late-stage ventures (not their stage) Summary Underdog Labs represents a relationship-driven, founder-centric pre-seed vehicle run by two co-founders with unmatched track record (25-year partnership, Expedia exit, 100+ successful investments). They excel at identifying mission-driven founders at the earliest stage and providing hands-on support to de-risk and accelerate. Their portfolio concentration in B2B AI, healthcare tech, and vertical SaaS reflects evolving market trends. Valued primarily for their operational playbook and founder network rather than brand recognition.