An AI seminar that produces a result
An AI seminar as a build day instead of a lecture, with compact input and most of the time spent on your own prototype on a real case.
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For most people, a seminar means slides, coffee and a handout that lands in a drawer. We rebuilt the seminar. Instead of lecturing, we let your team build. At the end of this AI seminar there is no slide deck, but a working prototype from your real data plus a documented record. We plan scope, challenges, roles, data, tool access and schedule together so your seminar can be ready to start within a week.
An AI seminar teaches knowledge about AI. At Corporathon, the seminar is rebuilt so participants do not just listen, but build on a real case, so the result is a working prototype and a documented competence record, instead of a slide deck with no application in daily work.
The problem this seminar solves
The classic seminar format is built for conveying knowledge, not application. That is exactly the weak point for a practical topic like AI. Four things stay open after a pure lecture seminar.
- Listening is not skill. A talk about prompts does not build a feel for it in your hands. Only doing it yourself builds confidence.
- No result. A seminar ends with a handout. Daily work stays the same the next day.
- Attention drops. In six hours of lectures, half the room switches off. Everyone stays engaged while building.
- No evidence with substance. A seminar slip proves attendance, not application.
Corporathon turns the seminar day into a build day. Input arrives exactly when it is needed and leads straight into a result.
What the seminar covers, specifically
This is not a lecture seminar and not a developer course. It is a guided build day for business teams who cannot code and do not need to. Participants work with Cursor, Lovable, n8n, Gamma, Figma Make, Claude Code and custom GPTs on their own data. The input is compact and practical; most of the time belongs to building.
A run has four building blocks that build on each other:
- 1A challenge instead of an agenda. The seminar topic becomes a real, tightly scoped use case with a named user and a desired output, for example "turn 40 weekly proposal PDFs automatically into a comparison table".
- 2Compact tool input. Instead of long lectures, each group learns exactly the tools its case needs, right before building.
- 3Build phase. The teams build with guidance. We sit alongside, unblock issues and show the next step.
- 4Pitch, evidence and handoff. Each team shows its result, hands it to an owner, and the seminar record carries real hands-on relevance.
Benefits and goals
The goal is a seminar that produces a result.
- A working artefact instead of a handout.
- Practical AI competence that emerged through building and therefore stays.
- A seminar record with hands-on relevance, not just an attendance confirmation.
- A documented AI competence measure as a building block for Article 4 of the EU AI Act.
Who it fits, and who it does not
| Good fit when | Not the best fit when |
|---|---|
| you want a seminar that produces a result | a plain keynote without application is enough |
| there is a real use case to build on | only a general AI overview is wanted |
| data and tool access can generally be approved | real data must never be touched for legal reasons under any circumstances |
| evidence with hands-on relevance is needed | a plain attendance confirmation is enough |
Services and deliverables
- Upfront scoping with challenge scope per group.
- Compact tool input and a curated stack per challenge, including access.
- A guided build day with facilitation throughout.
- At least one working prototype per team.
- A handoff document per prototype with owner, access, open risks and next step.
- A seminar record with hands-on relevance and a documented competence measure per participant.
Formats as offer cards
Spark
- What you get: 1 seminar day as a build day, a prototype, compact tool input, handoff document, seminar record with hands-on relevance.
- You work with: one Corporathon facilitator, the right stack for one challenge.
- Ideal for: up to 10 participants, a team that wants a seminar with a result.
- Your investment: on request.
Ignite (recommended)
- What you get: 2 seminar days, several challenges in parallel, several prototypes, seminar records, broader impact across the team.
- You work with: several facilitators, a curated stack per challenge.
- Ideal for: 10 to 15 participants, a department that wants a productive seminar.
- Your investment: on request.
Blaze
- What you get: 3 to 5 seminar days, several teams, deeper prototypes, seminar records with a clear implementation path.
- You work with: a facilitator team, the full tool stack, an optional link to an implementation sprint.
- Ideal for: 15+ participants, several departments with a company-wide seminar plan.
- Your investment: on request.
Teams from Adobe, YOYABA, Onventis and NavVis have worked with us. Prices on request for now; the scope depends on team size, number of challenges and depth of handoff.
AI seminar with a result vs. lecture seminar
| Criterion | Classic lecture seminar | Corporathon AI seminar with a result |
|---|---|---|
| Format | slides, lectures | compact input plus building |
| Result | a handout | a working prototype you keep |
| Attention | drops over the day | stays through your own build |
| Evidence | attendance | a seminar record with hands-on relevance |
| Proof of ROI | hardly provable | a tangible artefact as the starting point for your own measurement |
| Time to first result | ends with the seminar | on the seminar day itself |
The table compares seminar formats, not providers, and deliberately contains no invented percentages.
How the seminar can pay off (a model, not a customer figure)
A seminar with a result delivers two things in one day: a learned skill and a tool. The model has three inputs: time per week for a recurring task, the share the prototype built on the seminar day takes off, and internal hourly rate times people affected. Formula: *hours saved per week × hourly rate × 45 weeks × people − one-off cost*. A worked example as a model. If a task costs two hours per person per week and the prototype takes off half of that, that is one hour per person. At a rate of 60 euros and ten people, that is 1 × 60 × 45 × 10, so 27,000 euros a year in freed-up capacity from a single seminar day. We do the real calculation in the discovery call.
Interactive seminar schedule planner: /en/ki-seminar/tools/ablaufplaner/.
Social proof
Teams from Adobe, YOYABA, Onventis and NavVis have worked with us. We show their names and logos as references and, where approved, workshop photos and public feedback. We deliberately publish concrete figures only once the source, method and period are documented and approved. Everything at /en/case-studies.
The process as an animated timeline, in 1 week
| # | Step | Owner | Output |
|---|---|---|---|
| 1 | Intro call | Corporathon + sponsor | clarified seminar goal, rough scope, date |
| 2 | Tools and challenges call | Corporathon + team leads | scoped challenges, tool choice per challenge |
| 3 | Finalising information and data | Client (IT, data protection) | approved data access, documented limits |
| 4 | Hackathon preparation | Corporathon | prepared environments, access, schedule |
| 5 | Tool workshop | Corporathon + teams | teams can operate their stack |
| 6 | Hackathon sprint | Teams (guided) | working prototypes |
| 7 | Result pitches and handoff | Teams + owner | results, handoff documents, seminar records |
Your Corporathon, in just 1 week.
30-minute discovery call: clarify the need, pick a challenge, set the schedule.
The calendar is embedded via Cal.com and only loads external content once you ask for it.
Frequently asked questions
Short answers to the questions that come up most before booking.
It is a seminar we rebuilt into a build day. The knowledge input is compact and practical; most of the time belongs to building on your real case. The result is an outcome, not just a handout.
No. Business teams build with AI tools without classic programming. We choose the stack so the challenge is solvable without prior knowledge.
Spark fits up to 10 participants, Ignite 10 to 15, Blaze 15 and more. We set the right scope in the discovery call.
Yes. Every participant receives a seminar record with hands-on relevance, because a prototype emerges on the seminar day, not just a lecture is heard.
We clarify data access and limits with your IT and data protection team before the start. Only what is approved gets used, and the limits are documented.
It can document a practical AI competence measure and so contribute to Article 4. It is not an official certificate and does not guarantee automatic compliance.