AI workshops - AI workshops that move teams from AI hype to grounded capability.
Almost every Swiss leadership team is now talking about AI and planning to invest, yet most teams still need practical guidance on data, tools, and reliable execution. Interest is high; operational readiness drops quickly behind it.
Super AI Labs runs facilitated workshops that close that gap. We bring the right stakeholders into the same room, align expectations, build confidence, and leave clients with a concrete, decision-ready shortlist of AI opportunities, covering both custom software we can deliver in-house and existing tools we would recommend for process optimization.
What we deliver - Practical outputs, not generic AI strategy
- Data discovery workshop: we map the business model, processes, and data landscape together with business and operations stakeholders, and leave the room with a prioritized list of AI leverage points framed against value, risk, and data readiness.
- ChatGPT and AI tools workshop: a role-specific, hands-on session for employees focused on effective prompting patterns, quality checks for real work, safe tool selection, and reusable playbooks each team can apply to day-to-day tasks.
- Developer workshop on reliable AI coding: how engineering teams can move fast with modern AI coding tools while keeping production quality, using reliable implementation patterns with AI copilots, review and verification workflows, and guardrails for architecture, security, and technical debt.
- A prioritized, decision-ready shortlist of use cases with a clear build-or-buy recommendation for each one, covering custom software we can deliver in-house, existing tools worth rolling out, and items worth deliberately deferring.
Best fit - Who this service is for
- Leadership teams aligning on an AI direction before committing budget, hiring, or selecting vendors.
- Business and operations stakeholders who need a structured way to evaluate where AI could reduce manual work or create additional capacity.
- Engineering and technical teams that want grounded guidance on how to use modern AI tools without compromising production quality, security, or maintainability.
Typical architecture - Designed for reliability, grounding, and operational handover
The exact stack depends on the problem, but these are the design principles we usually optimize for.
- Modular formats. Each workshop format can be run on its own, combined with others, or shaped into a bespoke session tailored to the client’s industry, workflows, constraints, and available data.
- Calibrated depth. Depth is adapted to the audience, from beginner-friendly business sessions for non-technical stakeholders through to advanced, implementation-focused workshops for engineering teams.
- Direct handover to delivery. Workshop outputs feed directly into our delivery process, so discovery, architecture, and production delivery can pick up from the prioritized backlog without a cold restart.
- Engineering-led facilitation. We come from an engineering and delivery background, so workshop outputs stay grounded in what can actually be shipped, operated, and maintained.
- Tool-agnostic recommendations. We are comfortable recommending existing SaaS or automation products when they are the right fit, rather than defaulting to custom builds for every problem.
- Focused on measurable outcomes. Most use cases we help identify lead to the same practical outcome: more output from the same team, lower operational cost, or both.
FAQs - Questions we hear early in the conversation
These are the kinds of questions that usually matter before a team commits to scope, architecture, and rollout.
Who should join the workshop?
A mix of decision-makers, process owners, and team leads usually works best. For technical sessions, we recommend including developers and engineering leadership so implementation constraints are captured alongside business context.
Can the workshop be tailored to our industry and data?
Yes. We adapt examples, exercises, and recommendations to the client’s workflows, constraints, and available data, and we are comfortable operating in regulated Swiss contexts.
Do we need advanced AI knowledge before joining?
No. We adapt depth to the audience, from beginner-friendly business sessions through to advanced technical workshops for engineering teams.
What do we leave with after the session?
A shared understanding of your AI landscape, a prioritized set of next steps, and a concrete direction for implementation or internal enablement, whether that means custom software, rolling out an existing tool, or deliberately deferring.
Related proof - Case studies, articles, and next steps
If this is close to what your team needs, these pages are the best next places to look.
AI software development
Where custom software makes more sense than an off-the-shelf tool.
See our delivery process
How workshop outputs feed into discovery, architecture, and production delivery.
Schedule a workshop
Start with a short scoping conversation about goals, timeline, team maturity, and workshop format.