Deckmatch

A deep dive on YCs nearly 5K companies reveals a secret to get in: copying another successful project. YC startups don’t have to be unique. Far from it. https://lnkd.in/gYptHQnK #ycombinator #techcrunch #startups

The amazing Walid Fayez Mustapha, PhD and I have built something interesting for Slush attendees - a market inteligence tool that shows you which products (and by extension, which companies) are most similar to yours who are also attending Slush. It's powered by the same proprietary AI engine we built for AlphaLens. Turns out when you analyze product data with the right lens, you surface competitive insights that aren't obvious from company-level analysis. Companies often compete at the product level, not the company level (think Slack vs Microsoft Teams, not Slack vs Microsoft). It's particularly useful if you're: Doing competitive research before Slush Looking for potential partners with complementary products Trying to understand where you fit in the broader ecosystem Currently offering this as a free tool for Slush attendees. Let me know if you'd find it useful - curious to hear your thoughts on what other insights you'd want to see.

Tldr; 🎉 we raised an oversubscribed seed round and have an awesome product we will be launching on stage at Slush next week 🙌 The internet took us from browsing directories to searching intent. But private market intelligence is still stuck in the Yellow Pages era. If you want to discover interesting companies today, you have to already know their names. You can't type "show me companies using AI to help nurses make better decisions." The data exists, but it's trapped in an unstructured mess of pitch decks, websites, and product specs. This struck me as absurd. We've mapped the human genome, but we can't map what companies are actually building? So we decided to solve this. We've created a platform that actually understands products - not just company metrics. The early results have been fascinating. When you structure the unstructured, you start seeing patterns in innovation that were previously invisible. Today we're announcing our oversubscribed Seed Round that sees us setting up shop in Palo Alto 🇺🇸 . But what's more interesting is what we're about to release: we're giving founders free access to this intelligence - Because understanding who is building in your space shouldn't require a $30k enterprise subscription. Founders head to -> alphalens.com The future of private market intelligence isn't about better databases. It's about better discovery. Grateful to Alliance VC & Luminar Ventures for seeing this vision early and with special thanks to Skyfall Ventures and First Degree for your trust and backing. Couldn't ask for better partners, as we set our sights on 🇺🇸 🙏 Arne Tonning, Louise Hagen, Reid Jackson, Kaan Anit, Preben Songe-Møller Cc: Walid Fayez Mustapha, PhD, Robin Wänlund Link to the story: https://lnkd.in/dc7p8bcu

Can we fully automate startup investing? It depends on the fund size and target stage. Here's a simple framework and the most suitable approach👇 #1 Micro/Solo GPs ➡️ Traditional (and Quant Followers) 📌Highest diversification (30+) 📌Tiny tickets (few hundred k) 📌Tiny funds (tens of millions) and little management fees 📌Flexibility to lead/co-lead/follow 📌Strong focus on geo/sector/communities/business models/etc. 📌Sourcing, screening, and access are key #2 Early ➡️ Augmented (and Quant Followers) 📌High diversification (30-40) 📌Small tickets (few millions) 📌Small funds (100-300m) and okayisch management fees 📌Focus to lead/co-lead 📌More generalist focus 📌Sourcing, screening, and access are key #3 Boutique ➡️ Traditional (and Augmented) 📌Medium diversification (20-30) 📌Medium tickets (few millions to few tens of millions) 📌Medium fund size (200-500m) and medium management fees 📌Focus on lead 📌Thesis-driven and medium focus 📌Sourcing, screening, access, and portfolio value creation are key; rely heavily on their reputation #4 Multi stage = Combination of Early + Growth #5 Growth ➡️ Quant (and Augmented) 📌Low diversification (10-20) 📌Big tickets (tens of millions to hundreds of millions) 📌Big fund size (billions) and big management fees 📌Focus on lead/co-lead/follower 📌Thesis-driven and medium focus 📌Screening, due Diligence, access and portfolio value creation are key; price matters a lot Read the full story in today's episode of Data-Driven VC

🚀 Introducing Custom Fields by Deckmatch! 🚀 We're thrilled to unveil our newest feature designed with you in mind. At Deckmatch, we understand that every investor has unique needs. Whether you’re focused on GMV, CAC, ARR, or other critical metrics, our Custom Fields feature lets you tailor our AI workflow to your specific requirements. 🔍 Why Custom Fields? Because every firm is unique. Custom Fields allows you to capture and structure the data that matters most to you, ensuring seamless integration with your CRM through our API-first approach. In our latest demo, we showcase: 1️⃣ Adding custom fields for specific metrics. 2️⃣ JSON output preview. 3️⃣ Seamless data reflection on deal pages and CRM integration. Ready to see how it works? Watch the video to see Custom Fields in action and discover how Deckmatch can tailor insights to your investment criteria. Deckmatch - Tailoring your investment insights. #Deckmatch #CustomFields #VentureCapital #InvestmentInsights #SaaS #FinTech #Innovation #APIIntegration #Startup Let's tailor your investment journey together! 🚀

Interested in joining Deckmatch and help us build something fundamentally novel and commercially viable? I can promise engaging challenges, a vibrant international team and a rewarding ride to the right candidate. #hiring #Python