Data Engineering Summit
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Logistics
Apple maps might take you to the wrong address. Please use Google maps to go to 5 Palo Alto Square. Light food and refreshments will be provided
Overview
Let’s cut to what matters: modern data engineering is less about sexy code and more about cleaning up after your data’s existential crisis. Meet:
Ari Morcos, Co‑founder & CEO @ DatologyAI—ex‑Meta FAIR and DeepMind maestro, Harvard PhD, whose startup builds fully automated, scalable tools to curate the right data for GenAI models (text, image, audio, you name it).
Hendrik Krack, AI Product Manager @ Aparavi—he helps tame unstructured data with a no‑code pipeline that processes 1,600+ file types, enforces compliance, and makes data “AI‑ready” without you needing to be a wizard.
Jiang Chen, Head of DevRel @ Zilliz—the force behind Milvus, the open-source vector database. An ex-Google search guru, he’s tackling the biggest bottleneck in AI: making billion-scale vector search affordable. His secret weapon? A new architecture that stops infrastructure costs from eating your AI budget alive.
Christopher Amata, Vector Solutions @ Pinecone—he’s the one you call when your RAG pilot project blows up in production. A veteran of scaling AI infrastructure, he specializes in architecting cost-effective, high-performance vector search systems that actually deliver on the hype.
These voices reflect the future: one stressing quality data for smarter AI, the other ensuring that messy data doesn't choke your models. No fluff, just substance.
Agenda