Mplify Member Summit – EMEA | Agenda

The Mplify Member Summit – EMEA convenes global thought leaders shaping the future of AI-ready, NaaS-enabled networks. Our fast-paced program presents a clear view of the state of the NaaS industry, with focused sessions on transport, automation, federation, and edge, along with deeper exploration of priority implementation topics such as Model Context Protocol (MCP) and NaaS for AI.



Wednesday, 10 June 2026 — Summit Conference Day

The Agentic AI Era – NaaS as the Infrastructure for AI

This day delivers presentations, demonstrations, case studies, and interactive sessions designed to drive insight, discussion, and action to prepare, optimize, and monetize networks for AI.

NaaS State of the Industry, Mplify Strategy and Work Programs

As a unifying alliance for NaaS, Mplify frames the agenda, establishes a shared view of industry progress, and defines the priorities needed to advance adoption in the AI era.

State of the Industry: Analyst Readout
NaaS for the Agentic AI Era: Mplify Strategy Overview
State of the Alliance: Building and Leveraging NaaS Ecosystems
Audience Discussion: Voice of the Mplify Membership

Transport for AI: Scaling NaaS with High-Performance Connectivity

AI workloads are placing new demands on transport networks. Explore how operators are monetizing existing assets and accelerating investment to support AI-driven services.

AI Training and Inference Demands and Transport Readiness
Wavelength, Carrier Ethernet, and Broadband Design Approaches
Industry Timelines for Composable, Elastic, and On-Demand NaaS for AI
Leveraging Mplify Transport Standards to Support NaaS Evolution

Automating NaaS for AI

Over more than a decade, Mplify has developed a comprehensive portfolio of Lifecycle Service Orchestration (LSO) APIs and product payloads that underpin multi-domain automation. This segment focuses on how these assets are being applied to support AI-driven services and accelerate ecosystem integration.

The LSO API Portfolio: Overview, Applications, and Success Stories
Evolution of Automation: From APIs to Intelligent, Context-Aware Models
LSO as a Model Context Protocol (MCP) Control Plane
Introducing Mplify AI Agent Implementation Guides

Edge Monetization & Federation Fabrics

As AI reshapes wholesale and interconnection models, explore the impact of sovereign AI, the evolution toward a federation of the future, and how new trust and commercial frameworks will support an AI-driven digital economy, as well as how Mplify members can prepare and participate.

Monetizing the Stack: GPUaaS and Model-as-a-Service
Federation Fabrics: Networks for an AI-driven Economy
AI Exchange and Interconnect Models
Certifying Trust in the AI Era



Thursday, 11 June 2026 — Summit Deep Dives

From Alignment to Implementation

Building on the Summit Conference Day, Thursday translates direction into execution across two priority areas: agentic AI for Lifecycle Service Orchestration (LSO) and NaaS for AI. Sessions draw on work advanced across Mplify’s programs and committees, with a focus on implementation approaches and priorities for the second half of 2026.

Agentic AI for Lifecycle Service Orchestration

Model Context Protocol (MCP), agent-to-agent interaction, and agentic AI are redefining how services are automated and coordinated across providers. This session focuses on how Mplify members are advancing agentic AI for LSO, applying LSO APIs and product and service payloads to support intelligent automation and multi-domain orchestration.

Topics include:

MCP Server reference designs and implementation approaches
Building AI agents using LSO APIs and product and service payloads
Orchestration and coordination of agent-driven workflows across domains
Verification, auditability, and trust for AI-driven interactions
Performance, reliability, and lifecycle management of agent-driven systems
Developer experience and tooling for AI-enabled automation environments

NaaS for AI

AI workloads are redefining what fit-for-purpose networking requires. This session focuses on how Mplify members are defining the attributes, use cases, and modular service models needed to support AI at scale.