AI Innovator Munich with Weights & Biases × AppliedAI
Building Enterprise AI Platforms at Scale
Leading organisations are quickly identifying how AI agents and models can transform their organisations but face significant challenges operationalising them reliably, compliantly, and at scale. Weights & Biases and AppliedAI are hosting an evening in Munich for senior AI leaders, engineers, and practitioners facing this challenge and ready to discover how to build an AI platform that makes agents and models both scalable and governed, without slowing down innovation.
Whether you are scaling a mature AI platform, building an AI governance framework from scratch, or working out how to make production AI repeatable across teams, the evening offers directly applicable insights across every stage of the AI journey.
What to expect
A practical, no-nonsense guide to AI governance and EU AI Act readiness - what technical leaders actually need to implement, not just what the regulation says
A blueprint for moving beyond isolated pilots and into production-grade AI systems that scale reliably across teams and the wider organisation
How robotics organisations are operationalising AI today, and the lessons enterprise teams can take directly back to their own platforms
Networking over drinks with Munich's senior AI engineering community
What you’ll learn
Governance as the foundation: how to translate EU AI Act requirements into real engineering workflows, embedding compliance into development from day one and building trust through transparency, evaluation, and auditability.
The AI control plane: obtaining an organisational, single layer of visibility and control across every model, application, or AI agent, by monitoring performance, running evaluations, and driving continuous improvement throughout their full lifecycle.
From POC to production at scale: the evaluation pipelines, observability practices, infrastructure patterns, and organisational readiness needed to make AI repeatable and reliable across teams.
Lessons from robotics: why robotics teams are ahead in operationalising AI, and how enterprise teams can apply their approach to managing real-world complexity, robust evaluation, and accountable AI platforms.
Who should attend
Senior AI & leaders
AI engineers, AI researchers & AIOps practitioners
Robotics & physical AI teams
Platform & Infrastructure
AI product leaders & managers
Anyone building, scaling, and operationalising production AI systems, aligning governance and compliance or accountable for AI strategy and outcomes
Featured talk from Weights & Biases
From physics to intelligence: Scaling robotics & physical AI
Robotics and physical AI systems introduce a new level of complexity to the AI lifecycle — combining simulation, real-world data, hardware constraints, and large-scale experimentation.
In this session, we’ll explore:
Managing experimentation across simulation and real-world robotics environments
Tracking multimodal data (vision, sensor, control signals) at scale
Evaluating embodied AI systems beyond traditional metrics
Building reproducible workflows for robotics and physical AI teams
We’ll share practical lessons from teams developing next-generation intelligent systems, and how modern tooling accelerates iteration from physics to deployed intelligence.