Accelerating AI Innovation with Dell Technologies and NVIDIA

Dell Technologies helps startups and scale ups modernise IT with simple, affordable, reliable solutions that grow with your ambitions. We’re bringing these insights to our 4YFN conference session, delivered in collaboration with our partner NVIDIA.

Join us to discover how Dell infrastructure and NVIDIA technologies together power secure, future ready platforms for AI, cloud and hybrid work, without the complexity or cost of traditional enterprise setups.

Hear from leading Dell and NVIDIA experts. Discover high growth customer success stories. Reserve your seat and walk away with concrete ideas to accelerate innovation and drive sustainable growth in your business.

09:00 - 09:30: Connect With NVIDIA Experts

Discover the most important NVIDIA news from CES for founders, builders, and ecosystem partners. This session distills the key themes, product directions, and partner opportunities shaping the next wave of accelerated computing and AI.​

09:30 - 10:00: Supercharge deskside AI development with Dell Technologies and NVIDIA

At 4YFN, discover how Dell Technologies and NVIDIA bring data‑center power to the deskside so founders and dev teams can prototype faster, cut cloud spend, and keep IP on‑prem while they iterate.
See how the Dell AI Factory with NVIDIA lets you start on a high‑performance workstation and scale the same stack into production—when traction hits—without re‑platforming.​

10:00 - 10:45: NVIDIA Inception Startups Showcase

Hear from NVIDIA Inception startups - ConfidentialMind, Gradium and MAbSilico - as they share how they are building accelerated computing and AI with Dell Technologies, what they have learned along the way, and the impact they are delivering for their customers. This session gives you a front-row seat to real-world innovation, from early vision to deployed solutions.

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10:45 - 11:00: Break

​11:00 - 11:45: Nemotron for Building Specialized AI Agents | Carlos Morais, EMEA Enterprise Developer Relations Manager​, NVIDIA

This session shows how startups can use the NVIDIA Nemotron family of open models, datasets, and recipes to build specialized AI agents that deliver high throughput and accuracy. You will also learn how the NVIDIA NeMo toolkit helps manage the full agent lifecycle—from generating high-quality synthetic data for domain-specific tasks to improving model reasoning with reinforcement learning. Founders and technical decision makers will see how these modular components provide a secure, scalable foundation for deploying production-ready products.​

11:45 - 12:00: Break

12:00 - 12:30: Galene.AI Makes Edge AI Productive the European Way: Sovereign, Private, Governed and Scalable  Andrea Cappelletti, Founder & CEO​, Galene.AI​

Most organizations don’t struggle with AI Adoption because models are weak. They struggle when adoption meets reality: shadow AI and data leakage, risk clearance and governance requirements, fragmented DIY stacks, and token-based economics that become unpredictable at scale. Galene.AI offers a different path with a private, sovereign AI platform—delivered as turn-key appliances designed and built with Dell Technologies—that runs inside the customer perimeter with runtime governance and per-GPU scaling and licensing.​

In this session, Andrea Cappelletti will show what ‘cloud-like but private’ looks like in practice, and why governance by design is key to enterprise adoption. He will also share how Galene.AI uses the latest NVIDIA technologies, including Blackwell and NVIDIA FP4 quantization, to maximize performance density from desk-sized to multi-rack enterprise configurations, improving efficiency, throughput, and responsiveness while maintaining strong model consistency.

12:30 - 13:00: Agents in healthcare: the hard parts (almost) nobody puts on slides | Alessandro de Sario, CEO & Co-founder, Therapyside | Ignacio Sarasua, Solutions Architect, NVIDIA

This session looks past polished demos to focus on what it really takes to run AI agents in live clinical environments. We'll unpack the hard problems teams face on the road to on-premises ambient AI—from integration with existing workflows and data sources to reliability, safety, and clinician trust—and share practical lessons from production deployments.​

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