
Rashad H
Pear VC Fellow @ Pear VC
About
About me: www.rashadhq.com Early-stage technology investor and operating partner specializing in B2B SaaS, AI/ML, and fintech infrastructure. Built HQ Ventures from solo angel to 410-member syndicate, deployed $1M+ across 10+ companies alongside tier-1 firms (FirstMark, Bain Capital, Draper). Advised three portfolio companies to successful follow-on funding rounds in 2025. Brings Fortune 100 operating expertise from leading $180M+ digital transformation initiatives at New York Life, combining venture investment acumen with hands-on value creation capabilities. MIT Sloan Fellows MBA. My unique background spans: - Building a 410+ member Venture Capital syndicate from zero - Implementing enterprise-scale AI and ML solutions in Fortune 100 - Leading post-merger integrations delivering 23% efficiency improvements - Developing data strategies that unlock new revenue streams - Building and managing high-performing technical and product teams
United States
Cambridge
Management Consulting
Deal Sourcing, Due Diligence, Early-Stage Startups, Investments, Strategic Business, Consultation, Entrepreneurship, Venture Financing, Python (Programming Language), Presentation Skills, Communication, Venture Capital, Analytical Skills, Strategy, Business Transformation, Business Analysis, Analytics, Data Visualization, Management Consulting, Digital Strategy
Experience

Angel Investor & VC Syndicate Lead
👼🏽
NOTE: Stage - Post Product, post revenue. Interested in companies building in the AI value chain: Chips > Data > Data Infra > Cloud and Inference > LLMsl | Agents > Verticialized SLM > Applications > Device etc. - Independent investor and advisor focused on B2B SaaS, AI/ML applications, and fintech infrastructure at seed/Series A - Deployed $0.8M across 10+ enterprise technology companies (2021-2025), averaging $10K-100K initial checks - Portfolio companies raised $25M+ in follow-on funding; 3 companies advanced to next funding round in 2025 - Evaluated 400+ investment opportunities annually, analyzing business models, unit economics, competitive positioning, and technical differentiation across enterprise software and AI platforms - Built 410-member investor network spanning operators, founders, and institutional investors for market intelligence, deal flow, and co- investment opportunities Select Investments & Value Creation: • Estuary (seed, 2022): Identified differentiated positioning in real-time data infrastructure before category emergence; advised on enterprise GTM strategy and facilitated client introductions; company raised a $17M Series A (3x markup) led by M13 (2025) • Brij (pre-seed, 2023): Backed founding team in digital product helping collect first party data and uncover customer insight via AI; company raised a $8M oversubscribed seed (3x markup) led by Pixel Capital and CEAS Investments • Kit (seed, 2023): Invested in a B2B at-home diagnostic testing platform; acquired by Ro within 6 months at 3.5x return INVESTMENT PHILOSOPHY: Focus on B2B SaaS and infrastructure where operating experience creates edge: AI value chain (infrastructure through agentic layers) where deployment matters more than algorithms; enterprise software with complex sales cycles; vertical SaaS/ AI in regulated industries. Technical AI background (NYU Stern) + Fortune 500 deployment enables evaluation of technical founders in markets where incumbents are vulnerable.

Supporter/Tiny Investor
New York, United States
As a data practitioner, love what Dave and team are doing to solve real-time data availability problem. Dave is the humblest of 2nd time founder with a successful exit. Happy to be small part of the journey! Investment Stage: Pre-Seed (recently raised Series A) Backed by FirstMark

Supporter/Tiny Investor
Queens, New York, United States
Lawtrades aims to change how your company utilizes legal resources. Happy to be a supporter and a small part of my friend Raad and his team's journey. Backed by Draper Associates, Social Capital, Graph Ventures, and Sahil Lavingia

Corporate Vice President
New York, New York, United States
New York Life ("NYL") is a Fortune 100 (Ranked #71) mutually policyholder owned company Leading NYL’s critical strategic initiatives around Products, AI & Analytics, and digital capabilities
Education

M.S. Thesis: Estimate real estate property prices for New York City through machine learning predictive analytics (regression, random forest, xgboost, neural network models etc.); achieved more accurate model results than Zillow Zestimate (comparing MAE or RMSE) Notable coursework: Modern Artificial Intelligence | Strategy Change & Analytics | Network and Platform Analytics | Data Visualization with Tableau & R | Digital Marketing Analytics | Foundation of Statistics and R | Big Data | Data Mining with R | Data Driven Decision Making | Decision Modeling & Decision Under Risks
Rashad H's Contact Information
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