Live presentation + demo:

RLC Pro AI: Maximize the throughput of your AI infra

Why the OS is where GPU ROI is won or lost, and how RLC Pro AI helps you win

April 2, 2026 | 2:00 PM ET | 60 minutes

Organizations are committing hundreds of millions of dollars to GPU infrastructure and running it on operating systems that were never designed for AI workloads. The OS underneath your GPU fleet determines how much performance the hardware actually delivers, and for most enterprises, that performance has been left on the table.


RLC Pro AI is purpose-built to change that. The CIQ Linux Kernel, GPU drivers, libraries, and frameworks ship tuned and validated together for AI inference workloads. No manual CUDA assembly. The same validated stack runs on bare metal, AWS, GCP, Azure, and sovereign on-premises infrastructure from first boot.


This session walks through why the OS layer is where GPU ROI is won or lost, how RLC Pro AI is architected to maximize output from the hardware enterprises are already running, and what production readiness actually requires at the OS level, with a live deployment walkthrough and Q&A.



4.2.26 RLC Pro AI Webinar - REGISTRATION

What you'll learn

  • Why the OS is where GPU ROI is won or lost: How the OS layer determines how much performance your hardware actually delivers, and what most Enterprise Linux distributions leave on the table
  • How RLC Pro AI is built differently: CLK and a CUDA + DOCA-OFED stack validated as a unit before shipping, so performance is consistent from first boot and across every update
  • How to deploy a production-ready GPU with RLC Pro AI: Live walkthrough of the path from install to inference
  • How the economics improve at scale: More output from the same hardware means fewer nodes to hit the same targets; how that math works at the node, cluster, and fleet level

Is this for you?

  • ML Engineering Leads and AI Platform Architects responsible for GPU infrastructure performance and production readiness

  • Linux Admins and SREs managing GPU-accelerated environments

  • CTOs, CIOs, and VPs of Engineering accountable for AI program delivery and making GPU investment defensible

 

Agenda preview

  • Why traditional Linux waits for patches, and how RLC-Hardened fights back
  • LKRG deep dive: runtime kernel protection that detects exploitation as it happens
  • The layered defense stack: how LKRG + hardened_malloc + hardened glibc make your foundation hostile to attackers
  • From 40+ hours to 30 minutes: automated STIG compliance in RLC-Hardened
  • Real ROI: how security-first architecture saves 1-3 FTEs annually
  • Live Q&A with our expert panel
Sovereign AI 01-28-26-Webinar-1