👋 Hi, I’m Andre and welcome to my newsletter Data Driven VC which is all about becoming a better investor with Data & AI. ICYMI, check out some of our most read episodes:

Welcome to another edition of our Sunday “Resources” stream where we share our most valuable data & resources across four rotating formats:

  1. 30 Hottest Startups of the Month (September’s list here)

  2. Top Downloaded Resources from The Lab #1 (how to prompt - the definite guide for investors, founders & operators here)

  3. State of the Market (see September episode here)

  4. Top Downloaded Resources from The Lab #1 (this is today!)

For 1. and 3., we collaborate with best-in-class partners to ensure you get the highest quality data. For 2. and 4., we leverage our ever-growing product portfolio and share selective snapshots of the most sought-after resources from The Lab.

Resources Start Compounding

In past “Resources” episodes we shared our top prompts for startup sourcing, screening & due diligence, and deal winning & closing, and various lists with active 312 family offices, 59 pension funds, 1513 angel investors, and 997 accelerators you should know.

Access these and more resources like our 50+ masterclasses, automation templates, Notion templates, copilots, and more via The Lab.

VC Co-Pilot for Deal Sourcing

In today’s episode, we’ll share access to one of our most watched recordings “VC Co-Pilot for Deal Sourcing” with panelists from Atomico, Activant, and TRAC.

As part of Vestberry’s Venture Intelligence Day earlier this year in NYC, the panelists dig into practical workflows (signals, ranking, thematic “one-pagers”), founder assessment via digital footprints and long-form personality cues, and why charisma, trust, and relationships remain non-automatable. They also unpack pitfalls (outdated data, echo chambers), adoption challenges inside firms, sector nuances (e.g., regulated markets), and share concrete cases.

Watch if you want to learn:

  • How leading funds use data to nudge timing, sharpen diligence, and avoid bias - without losing the human edge

  • What early signals actually correlate with outliers - and why access beats prediction

  • The tech stack, costs, and culture shifts required to make AI your “analyst,” soon your “associate”

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