GenAI Zürich 2026

Conference Schedule

Experience over 120 sessions across multiple stages at GenAI
Zürich 2026, the European Summit on Applied Generative AI

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Day 1
1 April 2026
Day 2
2 April 2026
Tech & Startup Stage
2nd floor – Zimmer 22
10:00-10:30
Building AI Infrastructure You Control
The Playbook for a Sovereign Model-as-a-Service Platform
Senior Specialist Solution Architect
@Red Hat

Relying on black-box AI APIs often means trading data sovereignty and cost control for convenience. This session provides a practical blueprint for architecting a private, sovereign Model-as-a-Service platform using powerful open-source models. Attendees will leave with a concrete playbook to master observability, enforce security policies, and transition from an API consumer to a platform provider.

The Sovereign AI Stack No One Else Can Switch Off
In April 2025, a US president had Microsoft block European Court of Justice accounts overnight. No negotiation, no warning, just a switch flipped from across the Atlantic. For European enterprises handling sensitive data under GDPR, FINMA, or the upcoming EU Digital Networks Act, this isn't a hypothetical risk. It's a preview. Yet 92% of European enterprise AI still runs on US infrastructure. Most "sovereign cloud" offerings are policy promises: contractual protections that can be rewritten or revoked. Architectural sovereignty is different: your hardware, your building, your data, your AI never leaving your infrastructure. In this talk, Alexander Zehetmaier shows what a truly sovereign AI stack looks like in production: OpenAI-compatible APIs running on enterprise-owned hardware, deployed today at European companies protecting journalistic sources and trade secrets, with an 83% median cost reduction versus cloud equivalents. The session culminates in a live open-source launch: Xinity's API Gateway goes from private to public on GitHub, on stage, making a European sovereign AI infrastructure stack freely available for the first time. Key takeaways: why policy-based sovereignty is theater, what architectural sovereignty looks like technically, and how to deploy it today.
11:00-12:30
Engineering Trust in AI Systems
Constraining AI Until It Works
Software Engineer
@SkipLabs
The compiler changed everything. Before it, programmers worked in assembly — painstaking, error-prone, impossible to scale. The compiler introduced a contract: if it finishes, the output works. You don't read the assembly. You trust it. That contract unlocked decades of software progress. Today, AI is writing more code than ever. But that contract is gone. Agents say "done" when the code is broken. Engineers spend more time debugging AI output than shipping. What if we could bring that contract back? In this talk, we'll explore how combining opinionated execution, reactive computation, and sound static analysis can restore deterministic confidence to AI-generated code — and what it takes to make "done" mean done again.
Towards Business Superintelligence
Managing Consultant
@D ONE
Superintelligence is increasingly perceived as sophisticated orchestration of autonomous, collaborating AI agents. While the potential for full process automation is widely recognized, the current immaturity of agentic systems requires a professional bridge between state-of-the-art research and reliable business integration. My approach to address this gap is by running a research lab in parallel with consulting work, allowing for the direct translation of academic findings, e.g. in automated information extraction, into production-ready enterprise solutions. The ultimate goal is Business Superintelligence: a practical reality where an ecosystem of agents understands a company’s strategy, data, and services as intimately as a human coworker can do. Achieving this requires a disciplined path: investing in agentic research, building robust data infrastructure, applications and services with rich CLIs, and taking responsible risks through well planned and executed pilots. To illustrate this, I will share the specific architectural choices and hard-won lessons from our recent retail deployments, providing a realistic look at what it actually takes to get agentic systems into production.
Building the Trust Stack for Multi-Agent Collaboration
Most enterprises haven't shipped multi-agent AI to production yet — but the ones that have are hitting a wall nobody warned them about. The bottleneck isn't intelligence; it's trust. The moment agents cross organizational boundaries, discovery, identity, shared semantics, and secure execution all break down. An analysis of 1,600+ multi-agent execution traces found that system design issues and inter-agent misalignment account for over 76% of all failures (Cemri et al., 2025). Drawing from hands-on experience building multi-agent systems in fintech, this talk presents a four-layer "trust stack" and maps each layer to real protocols at different maturity stages: Agent discovery via A2A and Agent Cards (a Linux Foundation standard with 150+ backing organizations); zero-trust federation patterns consolidating from the ACP-into-A2A merger; Verifiable Semantics to prevent silent "semantic drift" failures; and AWCP for secure workspace delegation when agents need to compute, not just chat. Attendees will leave with a clear architectural model for layering trust into multi-agent systems, an honest maturity map — what to deploy now, what to design for, and what to watch — and concrete failure patterns to avoid when crossing organizational boundaries with agents.

More sessions to be revealed soon...

13:30-14:00
Agentic AI & MCP: From System Migration to Unified Interfaces
Migrating Complex Systems with Agentic AI

Over 10,000 SAP BW systems face end-of-support by 2030 — a migration challenge so complex that traditional automation cannot scale to meet it. Manual migrations take two or more years, are error-prone, and require scarce expertise. We're using agentic AI to change that.

We'll show how multi-agent systems reverse-engineer legacy platforms, construct knowledge graphs of thousands of interdependent objects, and autonomously generate complete modernized systems — including the migration tooling itself.

Our three-phase framework — Reverse, Rethink, Rebuild — is a generalizable pattern for any complex system transformation, compressing years of work into months with automated validation at every step.

Attendees will leave with practical insights on multi-agent orchestration, knowledge graphs for spec-driven-development, synthetic data strategies for safe testing at scale, and hard-won lessons about where AI excels versus where human judgment remains essential.

Grounded in production experience, not theory.

The End of Tool-Hopping: Agents, MCP, and the Rise of Unified Enterprise Interfaces
Enterprises have spent decades trying to connect systems, yet teams still jump between tools, duplicate work, and struggle to trust their data. What if the problem was never integration itself, but how we interact with our systems? In the age of Gen AI and agent-driven architectures like MCP, we finally have a way to unify that experience.
14:00-15:30
Roundtable
Roundtable
Tech
Tech
Tech
Tech
Geneva 2027 AI Summit Roadmap: GenAI Zürich Checkpoint (invite-only)

An invite-only roundtable bringing together policy, research, and industry leaders to brainstorm Switzerland's approach to the Geneva AI Summit 2027. The session focuses on how Switzerland can leverage its distinctive strengths – open debate culture, interdisciplinary cooperation, and pragmatic governance – to shape international AI dialogue and deliver tangible outcomes.

Key discussion threads:
- Identifying Swiss strengths that can anchor the summit's focus and differentiate its outcomes
- Mapping where international stakeholders most urgently need dialogue, progress, and concrete deliverables
- Assessing potential partners and political dynamics around specific goals
- Developing concrete tools, instruments, and solutions as "Swiss contributions" to global AI challenges
- Applying Swiss values of diversity, subsidiarity, and cooperative spirit to both the summit's substance and its preparatory process

The roundtable follows Chatham House rules. Participants are encouraged to come prepared with perspectives on what Geneva 2027 should deliver and where Switzerland is uniquely positioned to drive progress.

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15:45-16:45
Startup Pitches
Bitter Lesson for Search
Task success in AI is the product of two things: information and intelligence. Intelligence has exploded. Search has not. The industry's answer, RAG, is a patchwork of human-engineered heuristics, and it's the same mistake the field has made before. Rich Sutton's bitter lesson tells us that general methods leveraging computation always win over clever hand-designed systems. We saw it in vision, we saw it in language, and search is next. SID trained an agentic search model end-to-end with reinforcement learning, replacing the entire RAG stack with a single model that reasons, retrieves, and iterates autonomously. For the first time, we show that search scales with compute.

More sessions to be revealed soon...

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