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Join peers for an afternoon of networking and hands-on learning. From smarter sourcing and fundraising to practical AI integration, you’ll take home proven tactics, hands-on demos, and real-world success stories you can deploy immediately.

Welcome to our monthly wrap-up episode where we cover August’s most relevant content at the intersection of startups, VC, data & AI👇

Welcome back after your summer break! Hopefully you recovered well and recharged batteries for an exciting H2-2025.

Despite everyone talking about a “summer hole”, specifically in Europe where OOO messages seem the norm across August, my summer was actually surprisingly busy with 2 new term sheets issued and several follow-on rounds closing. The most ambitious founders don’t sleep!

Also the public markets didn’t pause. Here’s the quick August snapshot. Full episode with all tables and deep dives here.

SVB’s latest State of the Markets report shows that ARR milestones for Series A doubled in the last four years. Here’s the key insights:

Maggie Basta’s analysis of the past three years of AI unicorn founders shows no single demographic or credential reliably predicts success. While some trends exist—such as a concentration of MIT alumni and roughly one in four holding a technical PhD—the long tail of variation dominates.

Andrew Chan highlights how leading VCs now treat AI as a “deal scout,” augmenting—not replacing—the human judgment at the core of investing. Firms use custom platforms and models like ChatGPT and Gemini to scan thousands of startups, parse pitch decks, and surface patterns or anomalies—work that once took analysts weeks now happens in hours.

They pair these AI systems with dashboards, scoring tools, and in-house datasets that flag promising companies or hidden risks early. Instead of replacing conversations with founders, AI frees partners to spend more time on judgment and relationships, while repetitive data crunching is automated. By training and refining these systems today, firms like EQT and Sierra Ventures are betting on compounding advantages—building a “venture factory” that scales precision without losing the human touch.

Fabian Mella Lukacs, founder of NeoVC, says that VC’s next transformation will be its own. Despite VC’s outsized impact—backing nearly half of all U.S. public companies before IPO—inefficiency is systemic. Early-stage funds waste thousands of hours each year on manual deal ops, costing the industry billions in lost productivity.

The pain is felt on both sides. Startups endure slow diligence, fragmented communications, and repetitive reporting. Investors juggle scattered CRMs, poor portfolio visibility, and LP reporting bottlenecks—stretching lean teams thin and limiting scalability.

NeoVC’s answer is an “all-in-one VC as a service” platform that unifies fund management, startup dashboards, LP reporting, and predictive analytics into one secure system. By blending automation, AI, and standardized workflows, it delivers clarity for LPs, focus for founders, and scalability for GPs. Just as fintech transformed public markets, this model could mark VC’s long-overdue transformation of itself.

USV recently posted their prediction about the future of VC as AI-augmented investing, where tools amplify human judgment rather than replace it. They believe the next generation of VC firms will be defined by how effectively they embed AI into their workflows—making learning faster, sourcing earlier, and operations sharper.

Just as they’ve backed transformative companies like Coinbase and Duolingo, USV is now rethinking its own operating model for the AI era, betting that those who experiment and build early will gain compounding advantages.