Wing Venture Capital — Investment Thesis & Preferences

Wing Venture Capital Research

Investment Thesis and Mission

Wing Venture Capital invests in companies building the AI-first technology stack—a generational transformation similar in scale and impact to digital, mobile, and cloud transitions. The firm's mission centers on "Enabling the AI-first technology stack," believing that businesses built on data, powered by AI, and put to work through increasingly autonomous applications will fundamentally reshape how companies operate and drive global economic growth.

The firm's foundational thesis is that the digital transformation of business, which dominated the past two decades, will be surpassed by an even larger AI-first transformation. Wing targets founders building at all layers of this stack: data infrastructure, AI tools and platforms, autonomous applications, and product-led growth (PLG) companies that accelerate adoption across these layers.

The AI-First Technology Stack

Wing has articulated a clear investment framework around five interconnected layers:

1. Data Layer (Foundation): Scalable, secure platforms to process, manage, and store data. These platforms serve as the "ground truth" foundation for all downstream AI and business operations. Examples from portfolio: Snowflake, Pinecone, Wherobots, Hydrolix, SFCompute.

2. AI Layer: Encompasses both proprietary AI technology development and integration of industry foundation models (LLMs, vision models). Developers build adaptation layers around foundation models and deploy proprietary models to improve fit with specific business processes. Examples: Deepgram, Voyage AI, Truera, Gradient, Goodfire.

3. Autonomous Applications Layer: Goes beyond simple workflow automation to automate everything that can be automated while arming humans with maximum context and insight for non-automatable decisions. These applications steer business processes toward optimal outcomes. Examples: Jellyfish, Outverse, Orby AI, Standard Practice.

4. Business Process Layer: Deep understanding of users, their goals, and target business outcomes. Embedded AI helps users make more informed decisions through better intelligence.

5. Product-Led Growth (PLG): The acceleration layer enabling faster adoption. Wing invests in companies using product-led growth to accelerate adoption of innovations across the entire stack. Examples: AirOps, Feathery, Tango, HeadsUp.

Specific Investment Areas

Wing focuses on six primary verticals within the AI-first stack:

Data Infrastructure: Database platforms, data warehousing, observability, analytics infrastructure, geospatial data
AI Applications: Autonomous agents, AI-powered tools, embeddings, LLM applications, computer vision
Autonomous Applications: Workflow automation, intelligent business process automation
Product-Led Growth: Developer tools, internal tools, and B2B SaaS with viral motion
BioXData: Intersection of biotech/life sciences and data/AI (precision medicine, genomics, therapeutics)
Emerging Areas: Web3, fintech, developer tools, security, healthcare

Stage and Check Size

Wing is an early-stage investor focused on pre-seed, seed, Series A, and early Series B companies. The firm's current investments show:

Minimum Check Size: $200K (evident from current data)
Maximum Check Size: $20M (evident from current data)
Typical Range: $1M-$5M for seed and Series A rounds
Investment Approach: Leads and co-leads rounds, often first institutional investor
Follow-on Strategy: Maintains follow-on reserve capacity to support portfolio companies through subsequent rounds

Lead Tendency

Wing actively leads rounds and frequently co-leads. The firm has demonstrated lead investor status across multiple portfolio companies including Deepgram, Pinecone, Snowflake, and others. Wing's partners maintain board seats and deep operational involvement with portfolio companies.

Recent Activity and Fund Status

Wing is actively deploying capital with recent investments across all focus areas:

Recent Notable Investments (2024-2025): Billables.ai, Arpelos Biosciences, Goodfire, Mendra, SFCompute, Zipline.ai, Tetra AI, Synt hefy, Utila
Fund Status: Actively deploying (Fund II appears to be in active deployment phase)
Deployment Pace: Consistent monthly/quarterly investments across portfolio
Investment Focus: Increasingly focused on AI infrastructure, autonomous applications, and developers building production AI systems

Portfolio Highlights and Track Record

Public Exits:

Snowflake (IPO, 2020) - Cloud data platform, $10B+ market cap
Seer (IPO, 2021) - Proteomics platform

Unicorn Companies (Estimated $1B+):

Gong (revenue intelligence, valued at $12B+ in secondary markets)
Cohesity (data management, $2.5B valuation)
Algorand (blockchain, multi-billion valuation)
CertiK (blockchain security, unicorn status)
StarkWare (blockchain privacy, unicorn status)
Human Interest (SMB 401k, unicorn status)

Major Acquisitions:

Aporeto → Palo Alto Networks (2019)
Around → Miro (2022)
Cumulus Networks → Nvidia (2020)
Moogsoft → Dell (2023)
Habu → LiveRamp (2024)
Noteable → Confluent (2024)
Upsolver → Qlik (2025)
Voyage AI → Acquired (2024)
GYANT → Fabric (2024)
Tetra AI → Qualcomm (2024)
Truera → Snowflake (2024)

Team and Operating Model

Founding Partners (4):

Gaurav Garg - works across all investment areas
Peter Wagner - builds AI-first tech stack
Sara Choi - bio x data and health focus
Jake Flomenberg - AI-first tech stack and PLG

Additional Partners (6):

Zach DeWitt (AI + PLG focus)
Tanay Jaipuria (AI applications + data infrastructure)
Chris Zeoli (data platforms, cybersecurity, AI infrastructure)
Rajeev Chand (Head of Research, community building)

Venture Partners (2):

Sunil Potti (cybersecurity, infrastructure, AI-native)
Ansuman Satpathy (data, computation, disease therapeutics)

Operating Partners:

Sunil Chokshi (Talent/recruiting - 100+ successful hires)
Rajeev Chand (Research, summits, community building)
Kayleigh Karutis (Marketing and brand)
Tiffany Tai (Business intelligence and benchmarking)
Sam Parker (Market development)

Decision Process and Timeline

Decision Structure: Partnership-based with partner specialization (domain experts make decisions in their areas)
Decision Timeline: Typically 2-4 weeks for seed stage; 3-8 weeks for Series A
Board Participation: Partners typically take board seats
Follow-on Approach: Regular participation in subsequent rounds with board observation/participation

Founder Support and Value-Add

Wing goes beyond capital, providing:

Founder Success Platform: Dedicated resources and connections for early-stage founders
Talent Program: Proprietary software to access IC talent pools; 100+ successful hiring placements
Market Development: Connection to technology leaders as advisors, customers, and partners
Research and Insights: Open-sourced research on AI trends, emerging industries, top-performing companies
Marketing Support: Launch PR, brand development, PLG fundamentals, user/customer acquisition
Business Intelligence: SaaS benchmarking and operational efficiency improvements
Community Access: Rajeev Chand leads high-level summits connecting founders with executives and potential customers

Geographic Focus

Primary: Silicon Valley (Palo Alto), US-wide
Secondary: Selected international (blockchain/crypto companies, European AI companies)
Expansion Interest: Increasingly global as portfolio companies scale internationally

Investment Preferences

Founder Preferences:

Technical founders with deep domain expertise
First-time founders backed by strong teams
Founders with product-market fit signals
Entrepreneurs with experience at scale-ups or hyperscalers (Google, Amazon, Stripe, etc.)

Company Stage Preferences:

Pre-seed: $250K-$500K (rare but selective)
Seed: $1M-$3M (typical)
Series A: $3M-$8M (frequent)
Series B: Selective follow-on (portfolio support)

Model Preferences:

Developer tools and infrastructure
B2B SaaS with technical buy-in
Product-led growth companies
Enterprise software solving specific pain points

Anti-thesis:

Pure consumer plays (with exceptions for AI-first companies)
Saturated markets without clear differentiation
Teams without technical depth
Companies without clear product-market fit path

Warm Introductions

Warm introductions are strongly preferred but not required. Wing partners actively participate in conference circuits and maintain deep networks. Portfolio company referrals carry significant weight.

Notable Public Appearances and Thought Leadership

Rajeev Chand hosts "Enterprise Tech 30" (ET30) annual summit
Regular content on AI trends ("From Words to Worlds," "Model Context Protocol," "Agentic AI Runtime Stack")
Partners speak at major conferences and publish research
Active Twitter/LinkedIn presence with market insights

Competitive Position in Market

Wing is a top-tier early-stage investor with:

Exceptional track record (Snowflake, Gong, Cohesity exits)
Deep technical expertise across founding partners
Strong operational support network
Access to tier-1 follow-on investors
Clear, differentiated investment thesis
Portfolio of 150+ companies across AI-first domains

The firm is well-positioned to attract the best early-stage founding teams building at the intersection of data, AI, and autonomous applications.