Author: Martin

• Infrastructure + Data Engineering Stage – Scalable infrastructure and data systems for AI
  

As European enterprises race to deploy scaling networks of interconnected digital workers, traditional data structures are hitting their absolute limits. To power the next generation of high-performing Autonomous Systems, organizations are completely rethinking their physical foundation and balancing intensive compute demands with strict latency limits and tight corporate budgets.

Addressing these foundational challenges head-on, the Infrastructure + Data Engineering Stage at the Nordic Data Science & Machine Learning Summit 2026 brings together the continent’s leading Platform Architects, Cloud Leads, and Data Engineers. This crucial track focuses entirely on the architectures, pipelines, and scalable computing environments required to support continuous Operational AI at a massive corporate scale.

This track targets the physical backend of enterprise AI, solving the friction between low-latency operational demands and skyrocketing overhead costs.

Key Technical Deep Dives:

• AI Infrastructure Economics: Data-driven playbooks on optimizing GPU utilization, fine-tuning inference costs, maximizing compute performance, and mitigating the immense scalability expenses of 2026’s real-time workloads.
• Model Context Protocol (MCP) Implementation: Discovering how this emerging open standard is being used to build universal, secure communication bridges between LLMs, tools, and historically siloed data infrastructure.
• Vector Database Scaling & Streaming: Engineering high-throughput, low-latency vector search architectures and streaming pipelines capable of processing millions of data points simultaneously for live operational environments.
• AI Ready Data Engineering Foundations: Transitioning away from traditional, static ETL processes toward highly contextual, real-time data pipelines engineered specifically for continuous machine ingestion and multi-agent interaction.
  

AI Infrastructure Economics and Scalability 

A major theme of this stage is AI Infrastructure Economics. Attendees will participate in deep-dives centered on optimizing GPU utilization, reducing heavy inference costs, and maintaining highly efficient hybrid cloud structures. Data professionals will explore the cutting-edge practices of AI Ready Data Engineering, learning how traditional data pipelines are being rebuilt into real-time, contextual feeding layers for machines. Sessions will highlight the practical value of the Model Context Protocol (MCP), demonstrating how this open standard unlocks seamless data interoperability across historically fragmented enterprise silos. 

Join 400 peer innovators at the Filadelfia Convention Center and be part of the largest Enterprise Applied Agentic AI Conference in the Nordics and Europe, to discover the concrete infrastructure strategies needed to fuel your scaling AI Agents and accelerate your enterprise-wide intelligent operations.

• Develop + Deploy  AI Stage – Building and scaling production ready AI systems
  

Across the Nordic region, forward-thinking technical teams are rapidly moving past basic chatbots and standalone RAG (Retrieval-Augmented Generation) loops. The current frontier belongs to Production-Ready AI architectures built on complex Multi-Agent Systems and self-healing, Intelligent Workflows. But shifting from single-prompt experiments to highly autonomous corporate software presents a brand-new set of engineering hurdles.

To connect those, the Develop + Deploy AI Stage at NDSML 2026 provides a rigorous, practitioner-led environment where developers, data scientists, and ML specialists can acquire the blueprints needed to build inherently reliable systems. This technical track strips away the standard vendor hype to tackle the actual software plumbing required to orchestrate, evaluate, and scale elite Compound AI Systems across modern corporate workflows.

Key Technical Deep Dives:

• AgentOps, MLOps, and LLMOps Integration: Building continuous delivery, deployment, and monitoring pipelines specifically designed for autonomous behavioral software.
• Advanced RAG & Context Engineering: Upgrading basic RAG (Retrieval-Augmented Generation) frameworks into resilient, agentic retrieval architectures that minimize retrieval latency.
• Hallucination Management: Implementing systemic testing, validation, and safety guardrails to detect and mitigate erratic model outputs before they reach production.
• Continuous AI Evaluation: Utilizing advanced metric frameworks and automated telemetry to execute relentless benchmarking and AI testing for complex operational systems.
  

The Technical Foundations of Agentic AI 

Engineers attending this dedicated track will explore the practical lifecycle of GenAI engineering, mastering the integration of MLOps and LLMOps to ensure smooth, repeatable deployments. A major focus of this stage centers on systemic error reduction, introducing advanced tactics for Hallucination Management and the development of continuous AI Evaluation testing frameworks. Attendees will gain firsthand exposure to the emerging discipline of AgentOps, learning how to capture system telemetry, monitor agent interactions, and orchestrate highly stable AI Agents. 

If you are looking to master the technical details of the Agentic AI shift and deploy systems your organization can genuinely trust, this is the place. Secure your ticket and join 400 of Europe’s leading tech minds on the biggest Enterprise Applied Agentic AI Conference in the Nordics and Europe at the Filadelfia Convention Center in Stockholm this November and visit the Develop + Deploy  AI Stage to see the scaling production ready AI systems and explore trustworthy, production-ready AI!

As autonomous technology moves from isolated testing environments into live operations, AI Governance has evolved from a secondary compliance requirement into a critical driver of business value. 

At the upcoming Nordic Data Science & Machine Learning Summit (NDSML) 2026, taking place on 10–11 November in Stockholm, the Manage + Govern AI Stage serves as the premier regional platform dedicated to this strategic balancing act. Designed specifically for CAIOs, risk managers, and business strategists, this track provides a plan for establishing Human-on-the-Loop Governance frameworks that protect enterprise assets without slowing down deployment momentum.

Turning “AI Policy” into “AI Performance”

This stage is the strategic center for leadership adjusting to the era of Operational AI. As organizations transition toward deploying AI Agents with real-world autonomy, traditional governance models are changing. This stage addresses how to build trust, measure ROI, and maintain compliance without suffocating enterprise innovation.

Key Operational Deep Dives:

• Human-on-the-Loop Governance: Moving past passive monitoring to engineer active human intervention points within scaling Autonomous Systems.
• Develop + Deploy: The practicalities of building Multi-Agent Systems, utilizing AgentOps, MLOps, and LLMOps, and mastering continuous AI Evaluation to combat reliability failures.
• Explainable AI (XAI) & Risk Mitigation: Techniques for stripping away the “black box” of Compound AI Systems, ensuring compliance officers can audit, evaluate, and trace machine logic.
• AI Operating Models: Restructuring corporate silos, upskilling teams, and ensuring clear AI ROI as digital workforces scale.
  
  

Unlocking Actionable Strategies for Enterprise AI Success

Attendees will dive deep into actionable corporate strategies, exploring how leading brands build AI operating models that effectively manage risk, guarantee data security, and comply with evolving frameworks like the EU AI Act. The sessions move far beyond basic theories to address real-world application, exploring how Explainable AI (XAI) can be leveraged to demystify complex corporate decision-making. By introducing continuous AI Observability directly into the management layer, attendees will learn how to accurately monitor systemic AI risk and unlock measurable AI ROI. 

Experience the Governance, trust, compliance, and operational AI readiness stage at the biggest Enterprise Applied Agentic AI Conference in the Nordics and Europe. Secure your pass for the Nordic Data Science & Machine Learning Summit 2026 and join 400 of Europe’s leading tech minds.