Christophe Tallec

Feldhoff & Cie invests in Europe’s most promising female founders Yesterday, Auxxo announced the first closing of Auxxo Female Catalyst Fund II, raising €26 million to invest in early-stage European startups with female founding teams. We are proud to be part of this commitment to expanding access to capital and driving lasting change in the venture landscape. Congratulations to Bettine Schmitz, Dr. Gesa Miczaika, the whole Auxxo Female Catalyst Fund team and all fellow investors who share this vision. Excited to see what we can build together! 

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I was delighted to participate in two panels at IPEM this year—one on “How AI is rewriting the PE playbooks” alongside Gaël Gibert from Advent and Guillaume Princen from Anthropic, and another on “Investing in the AI revolution” with Lauriane Requena from KKR and Astrid Moullé-Berteaux from Headline. At Seven2, we see AI not as a buzzword, but as a true industrial revolution—akin to electricity in its transformative potential. The real opportunity for private equity isn’t in chasing the next unicorn, but mostly in helping established companies harness AI to drive operational excellence and margin expansion. Our focus is on the “boring” but powerful applications of AI: automating repetitive tasks, optimizing processes, and leveraging proprietary data to revisit business models and create defensible advantages. The question for investors is not whether AI will change the landscape, but whether you want to own the companies before or after that transformation. We’re building the next generation of AI-enabled market leaders and keep an eye on AI-native companies that combine robust AI applications with high-value services. These businesses are particularly attractive for LBO: they already generate EBITDA, have a clear and growing role in supporting traditional companies to adopt AI, and are resilient against being displaced by hyperscalers. Stay tuned for more on how we’re putting this vision into action. #IPEM #PrivateEquity #AI #ValueCreation #Seven2

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The 🇪🇺📲 EUDI Wallet is one of the most ambitious projects Europe has ever started. We’ve made great progress — but still need to improve the user experience ⬇️ In my latest blog, I cover: ✅ Why UX will decide adoption ✅ How citizens should experience the wallet ✅ What organizations need for seamless integration ✅ Why ecosystem alignment is key The goal: a wallet that is simple, secure, trusted and used every day by everyone. But here’s the real question: 👉 What do YOU think we need to focus on to make the EUDI Wallet a success for millions of people? Read my comprehensive User experience guide here: https://lnkd.in/gkBGYCGG #eIDAS, EU Digital Identity Wallet #EUDIWallet

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🚨 The battle for the future of software is no longer about who can write code fastest — it’s about who owns the data and context to power AI. Generative coding agents and tools from Anysphere, GitHub Copilot, Windsurf Cognition and poolside are commoditizing software development. In this new era, context is king and data is the moat. Winners will be those who: 1️⃣ Embed deeply into workflows to capture rich, high-fidelity data 2️⃣ Engineer context precisely at inference time 3️⃣ Reinforce models through usage, not static prompts Legacy SaaS vendors face eroding moats. AI-native apps with data flywheels and contextual intelligence are rising fast. 👇 Full article in the comments. If you’re building in this space, I want to hear from you. Thank you to Jeff Haynie, Jason Warner, Çağla Kaymaz and Vedant Agrawal for providing input and feedback on this article! #AI #Software #VC #DeveloperTools #ContextIsKing #FutureOfWork

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LP Tech is now a category. And we have the Oxford paper to prove it: Ludovic Phalippou has published "𝘓𝘪𝘮𝘪𝘵𝘦𝘥 𝘗𝘢𝘳𝘵𝘯𝘦𝘳𝘴 𝘷𝘴 𝘜𝘯𝘭𝘪𝘮𝘪𝘵𝘦𝘥 𝘛𝘦𝘤𝘩𝘯𝘰𝘭𝘰𝘨𝘪𝘦𝘴." It's about the unique role of AI in private markets... and why LP Tech infrastructure is fundamentally different. 𝗧𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺: LPs face a mismatch between their data and what AI needs: • Private equity takes 10+ years to validate predictions,  • Public markets validate models in real-time • Disclosures arrive quarterly, 3-6 months late • Every GP uses different formats AI algorithms are built for abundant, high-frequency data. Private markets offer the opposite. 𝗕𝘂𝘁 𝘁𝗵𝗲𝗿𝗲 𝗶𝘀 𝗺𝗮𝘀𝘀𝗶𝘃𝗲 𝗽𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹: Phalippou's research shows GP narratives contain predictive signals. Fundraising documents and quarterly reports can forecast performance, if you can extract them systematically. The problem isn't lack of information. It's that information resists standardization. And that is the potential of new technology. 𝗧𝗵𝗲 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗹𝗮𝘆𝗲𝗿: The paper (partially) maps the LP tech ecosystem, many of whom are participating in this week's LP Tech Summit - and references our summit as evidence of a rising tide. Because LP tech isn't just a new breed of SaaS. The companies shaping this space represent a new infrastructure for transforming heterogeneous disclosures into structured intelligence. And that intelligence will shape and deliver private market returns for the good of everyone invested in the world's most important Limited Partners. 𝗧𝗵𝗲 𝗰𝗼𝗻𝘀𝘁𝗿𝗮𝗶𝗻𝘁𝘀: Some GPs now prohibit LPs from using LLMs on their documents. This could lock valuable unstructured data back into analog form before AI adoption scales. That should change. 𝗪𝗵𝘆 𝗜𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 𝘀𝗼 𝗺𝘂𝗰𝗵: LP Tech exists because private markets have a structurally different data problem. You can't apply public market AI tools and expect them to work. Phalippou's paper gives academic validation to what practitioners know: LP operations require purpose-built infrastructure. The category is real. And we're all just getting started! 🚀 🚀 Thanks so much to Dr. Phalippou for his work, and double thanks to Riley Thomas for sharing the paper with me. Read it in full you won't be disappointed.

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