NetAI GraphIQ Demo with Irfan Lateef
In this functional architecture deep dive, Irfan Lateef, Sales Engineering and Business Development lead, demonstrates the practical application of NetAI’s graph neural network (GNN) for large-scale networking. Lateef details the platform’s multi-layered ingestion process, which pulls configuration data via SSH CLI to build a comprehensive graph of the network, alongside real-time telemetry from SNMP, Syslogs, […]
NetAI Graph Neural Network Deep Dive with Deepak Kakadia
In this session, Dr. Deepak Kakadia, founder and CEO of NetAI, discusses the technical architecture of NetAI’s graph neural network (GNN) and how it provides deterministic root cause analysis for autonomous network operations. Kakadia leverages his experience at Sun Microsystems, Verizon Labs, and Google to explain why traditional AIOps and Large Language Models (LLMs) often […]
NetAI Deterministic Root Cause for Autonomous Network Operations
In this session, Mike Hoffman, co-founder of NetAI, discusses the critical role of deterministic root cause analysis as a prerequisite for safe autonomous network operations. He explains why current AIOps solutions still necessitate manual intervention and how NetAI’s graph neural network (GNN) technology provides a verifiable diagnostic layer that bridges the gap between observability and […]
Selector 2026 Roadmap and Q&A
Selector AI introduces an AI-powered network observability platform designed to unify multi-domain signals into actionable root cause analysis (RCA). The platform focuses on reducing the Mean Time to Repair (MTTR) by addressing the alert storm and fragmented data silos that plague modern network operations centers (NOC). By employing a three-layered approach of collection, correlation, and […]
Hammerspace Presents at AI Field Day 8
Solidigm Presents at AI Field Day 8
Scality Presents at AI Field Day 8
HPE Presents at AI Field Day 8
Cisco Presents at AI Field Day 8
Selector AI Presents at AI Field Day 8
Selector Platform Diagnosis Demo
Selector AI introduces an AI-powered network observability platform designed to unify multi-domain signals into actionable root cause analysis (RCA). The platform focuses on reducing the Mean Time to Repair (MTTR) by addressing the alert storm and fragmented data silos that plague modern network operations centers (NOC). By employing a three-layered approach of collection, correlation, and […]
One View, Total Clarity with Selector
Selector AI is an AI-powered network observability platform that unifies signals across multi-domain environments to provide intelligent outcomes and root cause analysis (RCA). The platform helps networking and infrastructure operation teams lower their Mean Time to Repair (MTTR) and improve operational efficiency by addressing the challenges of fragmented data and tool sprawl. Through a three-layered […]
Futurum Research Presents at Security Field Day 15
Dell Technologies Presents at Security Field Day 15
Fortinet Presents at Security Field Day 15
Netris Day Zero Demo with Alex Saroyan
This presentation provides a technical demonstration of the Netris controller’s capabilities in automating and simulating large-scale AI networking environments. The demonstration highlights the platform’s Day Zero functionality, where network engineers can model complex topologies and validate designs before physical hardware even arrives. By utilizing Terraform and the Netris CloudSim, Saroyan illustrates how a controller can […]
Consuming AI Networks with Netris
This presentation focuses on the consumption model of AI networks, specifically helping network engineers enable self-service capabilities for AI factory and neocloud operators. Alex Saroyan argues that while network engineers manage complex physical infrastructures, the consumers, such as compute orchestration products, require a simplified cloud-like abstraction. Netris achieves this through its Network Automation, Abstraction, and […]
Netris and the Lifecycle of AI Networking
Alex Saroyan, CEO and co-founder of Netris, provides insights from the company’s experience in deploying and automating large-scale GPU clusters. This second part of the presentation focuses specifically on the life cycle of AI networking, emphasizing that sustainable AI business strategies require architecting for long-term growth and newer GPU generations rather than single-cluster deployments. Saroyan […]
Netris Introduction and Overview with Alex Saroyan
CEO and co-founder Alex Saroyan discusses the evolution of network engineering in the era of AI. Saroyan highlights that AI networking significantly differs from traditional data center networking due to the massive scale of GPU clusters, ranging from 1,000 to over 50,000 GPUs, and the sheer density of network switches involved. Netris introduces the concept […]
Upscale AI’s Point of View with Aravind Srikumar
Upscale AI distinguishes between two critical domains: scale-up networking, which creates a large compute environment within a rack where multiple GPUs see a flat, unified memory, and scale-out networking, which connects these domains through memory copy operations. The presentation highlights that the network has become the backplane of a distributed ecosystem, moving from a standard […]
Upscale AI and the AI ASIC Landscape
Upscale AI posits that traditional data center networking is a round peg in a square hole for AI, as existing infrastructures were designed for general-purpose web traffic rather than the massive, synchronized communication required by billions of parameters and trillion-token models. By focusing exclusively on AI traffic and removing the bloat of legacy enterprise features, […]