AI certification with real hands-on evidence
AI certification as a repeatable standard, a prototype behind every record. For several cohorts, hands-on. Ready to start in 1 week.
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A certificate and a certification are not the same thing. A certificate is a single document. A certification is a repeatable standard by which you qualify and provide evidence for cohort after cohort in the same way. This standard ties every record to a self-built prototype, so a certification run always stays provable. We plan scope, challenges, roles, data, tool access and schedule together so a run can be ready to start within a week.
An AI certification is a repeatable standard by which teams are qualified and given evidence in the same way. At Corporathon, this standard ties every record to a self-built prototype, so every cohort is certified provably. It is not an official examination certificate, but it can document a competence measure for Article 4 of the EU AI Act.
The problem a real certification solves
Anyone who wants to certify many employees needs more than a one-off certificate. Without a repeatable standard, four problems emerge that grow with every further cohort.
- No consistent level. Every training runs differently, so the record means something different for every cohort.
- No provable core. If only attendance stands behind the certification, the whole standard is an empty shell.
- No scalable process. A format that cannot be repeated cleanly gets expensive and slow with every round.
- No comparison across cohorts. Without the same approach, results from different groups cannot be compared.
Corporathon turns certification into a repeatable standard with the same process, the same evidence criteria and a prototype as the provable core in every cohort.
What the certification covers, specifically
This is not a multiple-choice exam system, nor a developer course. It is a repeatable, guided qualification standard 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 process is built to repeat identically, cohort after cohort.
A run has four building blocks that build on each other:
- 1Standardised challenge scoping. Every cohort gets a real use case scoped by the same pattern, with a named user and a desired output.
- 2Tool workshop. Each group learns exactly the tools its case needs, following the same structure.
- 3Build phase. The teams build with guidance. We sit alongside, unblock issues and show the next step.
- 4Evidence by fixed criteria. Every cohort is certified by the same evidence criteria, tied to its prototype, so results stay comparable.
Benefits and goals
The goal is a certification standard that stays provable and comparable across cohorts.
- A repeatable standard with the same process and the same evidence criteria.
- A prototype as the provable core in every cohort, not just attendance.
- A consistent competence level across all certified groups.
- A documented AI competence measure per participant 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 to certify several cohorts by the same standard | a one-off certificate for one team is enough |
| the certification needs a provable core | a plain attendance confirmation is enough |
| data and tool access can generally be approved | real data must never be touched for legal reasons under any circumstances |
| a consistent, comparable level is required | an officially recognised examination certificate is required, which we do not issue |
Services and deliverables
- Standardised upfront scoping with the same challenge pattern per cohort.
- A curated tool stack per challenge, including access, built the same way each time.
- A facilitated build sprint with guidance throughout.
- At least one working prototype per team as the provable core.
- A handoff document per prototype with owner, access, open risks and next step.
- A certification record by fixed criteria and a documented competence measure per participant.
Formats as offer cards
Spark
- What you get: 1 day, one cohort, a prototype as the provable core, a certification record by fixed criteria.
- You work with: one Corporathon facilitator, the right stack for one challenge.
- Ideal for: up to 10 participants, a first cohort to test the standard.
- Your investment: on request.
Ignite (recommended)
- What you get: 2 days, several groups in parallel, several prototypes, certification records by the same standard.
- You work with: several facilitators, a curated stack per challenge.
- Ideal for: 10 to 15 participants, a department establishing a repeatable standard.
- Your investment: on request.
Blaze
- What you get: 3 to 5 days, several teams, deeper prototypes, certification records with a clear implementation path, a standard for repetition.
- You work with: a facilitator team, the full tool stack, an optional link to a recurring series.
- Ideal for: 15+ participants, several departments with company-wide certification across several cohorts.
- Your investment: on request.
Teams from Adobe, YOYABA, Onventis and NavVis have worked with us. Prices on request for now; the scope depends on the number of cohorts, team size and depth of handoff.
AI certification vs. a one-off certificate
| Criterion | One-off certificate | Corporathon AI certification |
|---|---|---|
| Reach | one team, one document | a repeatable standard across several cohorts |
| Evidence core | often just attendance | a prototype by fixed criteria |
| Comparability | none | the same process, comparable results |
| Level | uneven per round | consistent across all cohorts |
| Scalability | new each round | a repeatable, clear process |
| Time to first run | weeks | ready to start in 1 week, result depending on scope |
The table compares types of evidence, not providers, and deliberately contains no invented percentages.
How the certification can pay off (a model, not a customer figure)
A repeatable standard pays off over the number of cohorts. The model has three inputs: number of cohorts per year, the benefit per prototype from one cohort, and the one-off setup effort for the standard, spread across the runs. As a model: if one cohort's prototype takes off one hour per person per week from a task, at a rate of 60 euros and ten people, that is 1 × 60 × 45 × 10, so 27,000 euros a year per cohort. Across three cohorts, that adds up, while the standard is only set up once. We do the real calculation in the discovery call.
Interactive criteria grid: /en/ki-zertifizierung/tools/kriterienraster/.
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 goal, standard framework, date |
| 2 | Tools and challenges call | Corporathon + team leads | standardised 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, criteria |
| 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, certification 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.
A certificate is a single document per participant. A certification is the repeatable standard behind it, by which you qualify and provide evidence the same way cohort after cohort, with a prototype as the provable core each round.
No. It is a standard that Corporathon sets up and runs, with a prototype as the evidence core. It is not a state examination certificate, but it can document a competence measure.
Yes. That is exactly what the standard is built for. Process, scoping pattern and evidence criteria repeat, so results stay comparable across cohorts.
No. Business teams build with AI tools without classic programming. We choose the stack so the challenge is solvable without prior knowledge.
We clarify data access and limits with your IT and data protection team before every run. Only what is approved gets used, and the limits are documented.
It can document a practical AI competence measure per participant and so contribute to Article 4. It is not an official certificate and does not guarantee automatic compliance.