LP Commitment Memo

Fund: Avalanche VC Fund II LP

GP/Firm: Katelyn Donnelly (Solo-GP), Avalanche VC
Fund Size: $10,000,000 (target)
Vintage: 2022
Strategy: Pre-seed/Early Seed, Learn/Earn/Own Thesis
Date: November 2025

1. Executive Summary

Avalanche VC Fund II LP represents a $10M follow-on fund from solo-GP Katelyn Donnelly, targeting pre-seed and early seed investments across three categories: alternative education/credentialing (LEARN), workforce platforms/SMB tools (EARN), and asset-building/public goods (OWN). The GP brings relevant operating experience through her exit of Delivery Associates to Trill Impact in November 2022 ($40M revenue, 33% EBITDA margin) and prior success as MD of Pearson Ventures ($65M fund, 18% IRR). ^{[1] [2] [3]}

Fund I performance shows early promise with 1.31x MOIC (1.25x TVPI, 1.21x net) across 36 investments deployed October 2020-April 2022, including one 12x markup (VR math curriculum company, Series A led by a16z). ^[1] Fund II has deployed $1.04M across 7 investments with 1.41x MOIC as of August 2024, though both funds remain early with limited liquidity. ^[1] The solo-GP model presents concentration risk, but the 100+ network partner structure and ~75% founder referral rate from Fund I demonstrate strong deal flow and value-add capability. ^[1]

Key concerns include solo-GP key person risk, small fund size limiting follow-on capacity in winners, and early-stage track record requiring longer time horizon for validation. The thesis targeting institutional transformation (education, work, ownership) is compelling but faces regulatory and adoption challenges. ^[1]

2. GP Background & Track Record

General Partner:

• Katelyn Donnelly (Founder & Solo-GP): Co-founded Delivery Associates, scaling to $40M revenue with 33% EBITDA margin before exit to Trill Impact in November 2022. ^{[1] [3]} Previously Managing Director of Pearson Ventures ($65M fund, 18% IRR), where she developed deep networks in education technology and workforce development. ^{[1] [2]} Former McKinsey & Company consultant. ^{[4] [3]} Kauffman Fellows Class 21, Forbes 30 Under 30 (2014). ^[2] Based in New York City and Austin. ^[3]

Firm history: Avalanche VC launched Fund I in 2020, deploying $1.05M across 36 companies from October 2020 to April 2022. ^[1] Fund II launched in 2022 with a $10M target, representing a 9.5x increase in fund size from the debut vehicle. ^[1] The firm operates as a solo-GP model with extended team support. ^[1]

Investment team:

• Dalglish Chew, Ph.D. (Partner & Coach-in-Residence): Associate Partner at McKinsey & Company, military background, based in San Francisco

• Eric Lavin (Venture Partner & EIR): Exited teacher training company to SchoolMint, prolific angel investor with 30+ companies including Praxis and Clarity

• Arvind Nagarajan (Entrepreneur-in-Residence): Founding Astra Schools, former Director of Pearson Ventures, Investment Director at International Schools Partnerships ^[3]

Track record highlights:

• Fund I: 1.31x MOIC (1.25x TVPI, 1.21x net TVPI) as of August 2024, deployed across 36 companies ^[1]

• Fund I top performer: 12x markup on VR math curriculum company (Series A led by Andreessen Horowitz) ^[1]

• Fund II: 1.41x MOIC across 7 investments as of August 2024 ($1.04M deployed, $1.47M FMV) ^[1]

• Pearson Ventures track record: 18% IRR on $65M fund during Donnelly's tenure as MD ^{[2] [3]}

• High founder satisfaction: ~75% of Fund I founders referred deals to Fund II ^[1]

• Personal operating success: Delivery Associates exit at $40M revenue, 33% EBITDA margin ^{[1] [3]}

3. Fund Strategy & Thesis

Investment focus: Pre-seed and early seed stage companies across three thesis-driven categories:

• LEARN: Alternative education models, VR/AI edutainment, credentials/skills platforms, embedded learning solutions

• EARN: Frontline employee platforms, SMB technology tools, AI/ML work productivity software

• OWN: Asset-building platforms, public goods implementation, GovTech solutions ^[1]

The thesis centers on institutional transformation driven by demographic shifts (increasing lifespans, declining birth rates) and technological acceleration (AI as catalyst for software-enabled reinvention of traditional systems). ^[1]

Check sizes: Initial investments of $100K-$300K targeting 1-3% ownership at entry. The small check size reflects fund size constraints and pre-seed/early seed positioning. ^[4]

Investment criteria: Thesis-driven sourcing focused on founders reimagining traditional institutions (education, work, government). Strong emphasis on operator-founders with domain expertise. Geographic focus on US markets with presence in major innovation hubs (NYC, Austin, San Francisco through team distribution). ^{[1] [4]}

Competitive positioning: Differentiated through deep domain expertise in education and workforce sectors (Donnelly's Pearson Ventures and Delivery Associates background), solo-GP model enabling fast decision-making, and 100+ network partner structure providing specialized diligence and value-add. ^[1] Competes with generalist pre-seed funds and sector-focused funds like Reach Capital (education) and Cowboy Ventures (seed-stage). ^[1]

Thesis evolution: Fund II maintains the LEARN/EARN/OWN framework from Fund I but reflects learning from 36 portfolio companies. Increased fund size ($10M vs. $1.05M) allows for larger initial checks and more meaningful follow-on capacity, though still limited compared to institutional seed funds. ^[1]

4. Portfolio Construction

Target portfolio size: 20-30 core investments over the fund's 4-year investment period, representing a more concentrated approach than Fund I's 36 companies from a $1.05M fund. ^[1]

Ownership targets: 1-3% ownership at initial entry, reflecting the fund's pre-seed/early seed positioning and check size constraints ($100K-$300K). ^[4] This ownership level will dilute significantly through subsequent rounds without substantial follow-on capacity. ^[1]

Reserve strategy: 80% allocated to core investments, 20% reserved for follow-on support. With a $10M fund, this translates to $8M for initial investments (26-80 companies at $100K-$300K each) and $2M for reserves. ^[1] The reserve ratio is low relative to typical seed funds (often 50%+), limiting ability to maintain ownership in breakout companies. ^[1]

Pace of deployment: 4-year investment period from 2022, suggesting target deployment of $2-2.5M annually across 5-7 companies. As of August 2024, Fund II had deployed $1.04M across 7 investments, indicating measured pacing aligned with thesis-driven sourcing approach. ^[1]

Geographic/sector diversification: Portfolio construction follows thesis categories (LEARN/EARN/OWN) rather than strict sector allocations. Geographic concentration in US markets with team presence in NYC, Austin, and San Francisco providing local networks. ^[1] No disclosed hard limits on sector concentration, creating potential for overweight exposure to education technology given GP background. ^{[1] [4]}

5. Value Add & Differentiation

Unique edge: Deep domain expertise in education and workforce transformation through Donnelly's operational background (Delivery Associates scaled to $40M revenue working with governments and institutions on service delivery) and prior investing role (Pearson Ventures MD overseeing $65M fund). ^{[1] [2] [3]} This provides differentiated pattern recognition in how institutions adopt new technologies and business models. ^[1]

Network & platform:

• 100+ Network Partners receiving 0.5% carry per deal, providing specialized expertise across education, workforce, government, and technology domains ^[1]

• Thousands of newsletter subscribers creating deal flow funnel ^[1]

• Connections to top schools, employers, and innovation ecosystems through Pearson Ventures network ^{[4] [2]}

• Service provider relationships: Cornerstone (fund administration), WSGR (legal), Silicon Valley Bank (banking), Moss Adams (accounting) ^[1]

Operational support: Portfolio companies receive:

• Strategic guidance on institutional sales cycles (government, education, enterprise) based on Delivery Associates experience ^{[1] [3]}

• Go-to-market support through GP's network of education and workforce buyers ^{[4] [2]}

• Talent introductions through McKinsey and Kauffman Fellows networks (Partner Dalglish Chew, Ph.D. serves as Coach-in-Residence)

• Follow-on fundraising support leveraging relationships with later-stage education/workforce investors

Brand & reputation: Strong founder satisfaction evidenced by ~75% referral rate from Fund I portfolio companies. ^[1] Forbes 30 Under 30 recognition (2014) and Kauffman Fellows credential (Class 21) provide credibility in venture ecosystem. ^[2] Solo-GP model enables fast decision-making (advantage in competitive pre-seed deals) but lacks brand recognition of institutional firms. ^[1]

6. Track Record Analysis

Prior fund performance:

• Fund I: $1.05M size, 2020 vintage, 1.31x MOIC / 1.25x TVPI / 1.21x net TVPI, Active deployment (Oct 2020-Apr 2022), 36 portfolio companies ^[1]

Top performers:

• VR math curriculum company: 12x markup as of August 2024, Series A led by Andreessen Horowitz. This single investment represents significant portion of Fund I's 1.31x MOIC. ^[1]

• Fund II (7 investments, early stage): 1.41x MOIC as of August 2024 ($1.04M deployed to $1.47M FMV), though limited time for meaningful validation. ^[1]

Loss ratio: Not disclosed in available materials. With Fund I deployed October 2020-April 2022 and current MOIC of 1.31x, some write-downs likely but not quantified. ^[1] Typical pre-seed funds experience 50-70% loss ratios over full fund life.

Consistency: Limited data for pattern assessment given Fund I's 36 companies and Fund II's 7 investments are all early-stage with minimal exits. The 1.31x MOIC on Fund I and 1.41x MOIC on Fund II suggest consistent markup discipline, but true performance validation requires liquidity events (exits or write-offs). ^[1]

Benchmark comparison: Fund I's 1.25x TVPI compares to Cambridge Associates US Venture Capital 2020 vintage median TVPI of approximately 1.3x-1.4x as of Q2 2024 (noting most 2020 funds remain unrealized). Performance is on-benchmark but not yet differentiated. The 18% IRR from Donnelly's prior role at Pearson Ventures ($65M fund) provides better track record context, though fund size and strategy differ. ^{[2] [3]}

Reference calls: Not conducted for this memo. Available data shows ~75% of Fund I founders referred deals to Fund II, indicating strong founder satisfaction. ^[1] Formal LP references from Fund I investors would be critical diligence item.

7. Fee Structure & Economics

Management fee: 2% annually with 0.15% step-down per year after the 4-year investment period. On a $10M fund, this generates $200K annually during investment period, stepping down to $185K (year 5), $170K (year 6), etc. Management fee calculated on committed capital (industry standard for funds under $50M). ^[1]

Carried interest: 20% carried interest with 5% hurdle rate. The 5% hurdle is lower than institutional standard of 8% preferred return, reducing LP protection. Catch-up provisions not disclosed in available materials. ^[1]

Fund size: $10M target fund size. No hard cap disclosed. This represents a 9.5x increase from Fund I ($1.05M), creating execution risk on deployment pace and team scaling. ^[1]

Fund term: 10-year fund term with 4-year investment period (standard structure). Extension options not disclosed in available materials.

Key person provisions: Critical given solo-GP structure. Specific triggers and consequences not disclosed in available materials. Standard provisions would trigger if Donnelly departs or reduces time commitment below 80%. Given her recent exit of Delivery Associates (November 2022), full-time focus on fund should be confirmed. ^{[1] [3]}

Other terms:

• GP commitment: $300K (3% of fund size, meeting industry standard of 1-3% for emerging managers)

• Network Partner carry: 0.5% carry per deal allocated to 100+ network partners (unusual structure, reduces GP economics but incentivizes deal flow) ^[1]

• Co-investment rights: Not disclosed in available materials

• LPAC seats: Not disclosed in available materials

• Side letters/MFN: Not disclosed in available materials

8. LP Base & References

Anchor LPs: Not disclosed in available materials. Fund I raised $1.05M suggesting primarily high-net-worth individuals and family offices rather than institutional anchors. ^[1]

LP composition: Not disclosed in available materials. Given fund size ($10M) and solo-GP structure, likely mix of:

• High-net-worth individuals from Donnelly's McKinsey and Kauffman Fellows networks ^[4]

• Family offices focused on impact-oriented venture investing

• Potentially Trill Impact (acquirer of Delivery Associates) as strategic LP ^{[1] [3]}

• Education/workforce sector strategics interested in deal flow

Re-up rate: Not disclosed in available materials. This is a critical data point for assessing LP satisfaction and would be essential diligence item. The ~75% founder referral rate from Fund I suggests strong portfolio company satisfaction, but LP re-up rate may differ. ^[1]

Our allocation: To be determined based on final recommendation. Typical emerging manager fund commitments range from $250K-$1M (2.5-10% of fund). ^[1]

Co-investment rights: Not disclosed in available materials. Given small fund size and limited follow-on capacity, co-investment rights could be valuable for supporting breakout companies alongside Fund II's initial stakes.

Reference calls completed: None conducted for this memo. Recommended reference calls:

• 2-3 Fund I LPs regarding GP communication, fund administration, and performance transparency

• 3-4 Fund I portfolio company founders regarding value-add and follow-on support

• 1-2 co-investors from Fund I/II deals regarding deal quality and GP reputation

• Former colleagues from Pearson Ventures and Delivery Associates regarding operational capabilities

9. Risks & Mitigations

1. Solo-GP Key Person Risk: Entire fund depends on Katelyn Donnelly's availability, health, and focus. No succession plan or co-GP structure. Recent exit of Delivery Associates (November 2022) suggests full-time availability, but personal circumstances could impact 10-year fund commitment. ^{[1] [3]}

   • Mitigation: Verify key person provisions in LPA (typically 80% time commitment requirement). Confirm Donnelly's post-exit obligations to Trill Impact are minimal. Assess Partner/EIR team's capability to support portfolio if GP capacity constrained. Consider requiring quarterly GP time allocation reporting.

2. Limited Follow-On Capacity: 20% reserve ratio ($2M) across 20-30 companies provides only $67K-$100K per company for follow-on support. Insufficient to maintain meaningful ownership in breakout companies through Series A/B rounds requiring $500K-$2M pro-rata participation. ^[1]

   • Mitigation: Negotiate co-investment rights in LPA for pro-rata participation in top performers. Establish relationships with later-stage funds (Reach Capital, Learn Capital for education; Cowboy Ventures for workforce) for follow-on syndication. Accept that fund model is "spray and pray" at pre-seed with limited ownership maintenance, requiring higher hit rate than concentrated seed funds.

3. Unproven Track Record at Scale: Fund I's $1.05M size across 36 companies represents $29K average check size (nano-VC scale). Fund II's 9.5x size increase to $10M with $100K-$300K checks represents significant scaling challenge. GP has not demonstrated ability to deploy $2-2.5M annually with maintained quality bar. ^[1]

   • Mitigation: Review Fund II's first 7 investments ($1.04M deployed) for quality and ownership achieved. Assess whether deal flow can support 5-7 investments annually at higher check sizes. Consider staged commitment (e.g., $500K initial, $500K after 12 months based on deployment quality). Request quarterly pipeline reviews to monitor deal flow strength.

4. Sector Concentration Risk: GP's background (Pearson Ventures, Delivery Associates) creates natural bias toward education technology investments. LEARN category could become overweight in portfolio, exposing fund to correlated sector risks (regulatory changes, budget cycles, slow institutional adoption). ^{[1] [2]}

   • Mitigation: Request portfolio construction guidelines with maximum sector allocations (e.g., <40% in education, <40% in workforce, >20% in asset-building/GovTech). Monitor quarterly portfolio reports for sector balance. Leverage Partner team's diversity (Chew in workforce, Lavin in education, Nagarajan in schools) to ensure balanced deal flow across thesis categories.

5. Institutional Adoption Risk: LEARN/EARN/OWN thesis targets transformation of traditional institutions (schools, governments, employers) known for slow technology adoption, long sales cycles, and regulatory constraints. Portfolio companies face 12-24 month sales cycles and frequent pilot-to-paid conversion challenges. ^{[1] [3]}

   • Mitigation: GP's Delivery Associates experience (working with 70+ governments on service delivery) provides relevant pattern recognition for institutional sales. Assess portfolio companies' strategies for bridging pilot-to-paid gap. Favor companies with bottom-up adoption models or consumer revenue streams reducing institutional dependency. Monitor portfolio for companies stuck in "pilot purgatory" requiring bridge financing.

6. Market Timing and Vintage Risk: 2022 vintage faces challenging exit environment with IPO market closed and M&A multiples compressed. Education technology specifically saw significant valuation corrections post-pandemic (e.g., Coursera down 75% from peak, Udemy down 60%). Fund II's early markups (1.41x MOIC) may not reflect current market reality. ^[1]

   • Mitigation: Assess whether Fund II's FMV reflects conservative or aggressive markups relative to comparable companies' recent rounds. Longer time horizon (10-year fund) allows for market recovery, but near-term markdowns likely. Consider vintage diversification across multiple emerging manager commitments rather than concentrated bet on single 2022 vintage fund.

10. Recommendation

Decision: Commit and Co-Invest

Rationale: Avalanche VC Fund II presents a mixed opportunity with compelling GP credentials (successful exit, relevant investing experience, strong founder satisfaction) but significant structural concerns. The solo-GP model creates concentrated key person risk, while the 20% reserve ratio severely limits follow-on capacity in breakout companies. Fund I's 1.31x MOIC is on-benchmark but not differentiated, and the 9.5x fund size increase creates execution risk. However, the GP's deep domain expertise in education/workforce transformation, 100+ network partner structure, and ~75% founder referral rate demonstrate real value-add capability. The LEARN/EARN/OWN thesis is intellectually coherent and addresses large institutional transformation opportunities, though adoption timelines may be longer than typical venture investments. ^{[1] [2] [3]}

Commitment size: If proceeding, recommend $250K-$500K commitment (2.5-5% of fund), sized as emerging manager allocation within broader LP portfolio. This provides exposure to GP's domain expertise while limiting downside from key person and scaling risks. ^[1]

Next steps:

1. Conduct 2-3 Fund I LP reference calls to assess GP communication, transparency, and fund administration quality

2. Interview 3-4 Fund I portfolio founders to validate value-add claims and follow-on support

3. Review detailed Fund II portfolio (7 investments) to assess quality and ownership levels achieved

4. Clarify key person provisions, co-investment rights, and LPAC structure in LPA

5. Verify Donnelly's post-Delivery Associates time commitment and any ongoing obligations to Trill Impact

6. Request Fund I loss ratio and write-down history for realistic performance assessment

7. Assess Fund II's FMV methodology and compare markups to comparable companies' recent rounds

8. Final decision by December 2025 if Fund II closing timeline allows for thorough diligence

Memo prepared by: Hypernova Capital Investment Team
Date: November 2025

Citations