I build the data infrastructure that makes enterprise AI practical.
As Co-founder and CTO at Scality, I lead technology strategy, architecture, and innovation for distributed storage platforms designed for AI data pipelines, cyber-resilient protection, and cloud-scale applications. My work sits at the intersection of object storage, distributed systems, performance engineering, and the leadership required to turn hard infrastructure problems into products customers trust.
I’m especially interested in how organizations design storage and data architecture for RAG, vector search, model training, inference, governance, and long-term resilience at scale. Over the years, I’ve helped build patented storage technologies and teams focused on durability, simplicity, and operational efficiency.
I write and speak about AI infrastructure, storage architecture, cyber resilience, and engineering leadership. Outside of work, I also stay close to creativity through music.
I also build GPTS, an AI-driven system that models and improves real-world decision-making through feedback loops, scoring, and interaction.
As QLC NAND densities reach 61TB and beyond, the storage industry is rapidly approaching a strategic crossover point with high-capacity HDDs. However, raw acquisition cost remains a significant hurdle for many enterprise users. This session presents a comprehensive joint study by Scality and the Samsung Memory Research Center (SMRC) introducing the "Performance TCO" (PTCO) model. We move beyond simplistic $/GB metrics by benchmarking real-world datasets across hundreds of diverse HDD platforms globally and comparing them directly against lab results obtained on SMRC QLC platforms. By examining 16KB cell alignment, Write Amplification Factor (WAF) in sequential SDS workloads, and high-throughput use cases like Veeam Backup & Replication targets, we illustrate how QLC is positioning itself as a vital economic and performance-driven alternative for modern high-density object storage environments.