From first contact to a finished prototype in 1 week
Next steps to your hackathon
The flow as a timeline, from first contact to the pitches.
- Intro call. We clarify your starting point, which teams join and what you want out of the week.
- Tools and challenges call. We pick the real challenges from your daily work and set the toolstack.
- Finalization. All info, access and data come together, cleanly and GDPR compliant.
- Hackathon preparation. We set up environment, examples and flow so there is zero friction on the day.
- Tool workshop. A compact hands-on start on the stack, right on your own case.
- Hackathon sprint. Teams build on their challenges, we coach live.
- Result pitches. Each team shows its prototype, what works goes straight into use.
How a hackathon runs
Day 1 starts with AI foundations and a tool workshop so everyone is on one level. Then team building and ideation, each team sharpens its challenge. After kickoff the first sprint begins. From day 2 it goes deeper, we give deployment prompts, teams get their prototypes running, present the solutions and we hand off with documentation. The goal is always the same, after 24 hours a running prototype, not a concept paper.
How we work
We run the facilitation from A to Z. Challenge selection, tool and credit setup, setting up the work environment, coaching on the day and a clean handoff afterwards. You do not deal with tech, flow or didactics. You bring your team and your real tasks, we bring the rest.
Services and packages
Spark, 1 day, up to 10 people. Ignite, 2 days, 10 to 15. Blaze, 3 to 5 days, 15 and up. Prices on request, depending on format and team size. To keep going, choose an AI Implementation Sprint (2 to 4 weeks), a Recurring Hackathon Series (quarterly) or an AI Enablement Program (3 to 6 months).
Deliverables
At the end of the week you have 3 to 5 ready-to-use prototypes, an impact report with the measurable benefit, a skills library for continued work, an IT handoff package for a clean transfer, and a handful of AI champions on the team who carry the knowledge forward.
Challenges
Teams start with real tasks from your daily work. Proven examples: an email reply assistant that pulls context from the inbox and drafts answers in your own tone. A daily briefing agent that bundles to-dos and commitments from mail and chat. A meeting-to-action-items tool from the transcript. An executive reporting autopilot that pulls data into a board-ready update. An internal knowledge bot on your own documents. Plus an onboarding assistant or a proposal generator, depending on the team.
FAQ
How long is the preparation on our side? Two short calls and providing access and sample data. That is all. We handle tool setup, environment and flow so your team can start right away on the hackathon day, without weeks of internal planning.
Does the hackathon run on-site or remote? Both. On-site we come to you, remote runs over video and shared work environments. We clarify which fits in the intro call. Either way the promise is the same, a running prototype at the end.
What happens after the pitches? What works goes straight into use. You get an impact report, skills library and IT handoff package. If you want to continue, add an AI Implementation Sprint or start a Recurring Hackathon Series.
How many teams can work in parallel? Depends on the format. Spark suits one small team up to 10, at Ignite and Blaze several teams work in parallel on their own challenges. We coach all teams live across the sprint.
Do we get an internal AI literacy measures record? Yes. A hackathon can document one practical measure. The format can contribute as a context-appropriate measure supporting AI literacy. The company must assess whether its overall program is appropriate for the relevant roles and risks. More on /en/eu-ai-act.
Training depth: why training matters only when it is applied
This domain needs to be the strongest answer for AI training in German search. The searcher expects structure, safety and a clear learning path. The better answer is: yes, there is tool input and didactic guidance, but training does not end at understanding. It ends with application. Every core page should explain how employees move from foundations to their own challenge and why the prototype is the real learning test.
Employee perspective, not only HR perspective
AI training wins when employees feel enabled, not examined. Strong pages therefore speak not only about certificate and duty, but about relief in daily work: less copy paste, better research, faster replies, clearer meetings, fewer manual reports. That makes the training domain more human and stronger than pure compliance communication.
Rechtlicher Hinweis / Legal note: Ein Hackathon und der hier beschriebene Kompetenznachweis können praktische KI-Kompetenzmaßnahmen dokumentieren, sind aber kein behördlich vorgeschriebenes Zertifikat und garantieren nicht automatisch die Erfüllung von Artikel 4. Das Unternehmen muss die Angemessenheit seines Gesamtprogramms rollen-, kontext- und risikobezogen prüfen. / A hackathon and the competence record described here can document practical AI literacy measures, but they are not an officially mandated certificate and do not automatically guarantee compliance with Article 4. The company must assess its overall program for the relevant roles, context and risks.