5 teams, 24 hours, we ended up with five working prototypes shipping this week.
Case study
Onventis
Engineering50 developers brought AI into their own delivery process in a single day. Code review and test generation run in production.
Built for
Social proof
What participants post on LinkedIn
Original posts from real Corporathon hackathons, embedded straight from LinkedIn.
View on LinkedIn
Key facts
100%
AI adoption
50
Developers upskilled
1 day
Sprint length
Industry
Procurement software
Team & focus
50 developers upskilled
Result
100% AI adoption
Format
Spark (1 day)
Starting point
Code review and test creation consumed senior capacity, while AI tooling was used only sporadically and without a shared standard.
Approach
- One day facilitated build sprint with the whole engineering org
- Tool stack setup and prompt standards for every developer
- Handoff documentation and closing demo with the team
Result
- Reviewable adoption across the participating team
- Code review tool and automated test generation in production
- A hackathon turned into lived engineering practice
Customer voices
What participants publicly say about the hackathon
Summarised takeaways from approved LinkedIn posts by teams that built with us.
From “I should really learn AI” to a shipped product, with zero coding experience.
No months of prep needed: a team, a bit of chaos, and it turned into a working product.
5 teams, 24 hours, we ended up with five working prototypes shipping this week.
From “I should really learn AI” to a shipped product, with zero coding experience.
After day one, people who had never opened a terminal were building in Claude Code.
Oke Wilhelm
NavVis
The biggest effect wasn’t the tooling, it was the mindset shift: “I can build this myself.”
NavVis Team
Marketing & ops
After day one, people who had never opened a terminal were building in Claude Code.
Oke Wilhelm
NavVis
The biggest effect wasn’t the tooling, it was the mindset shift: “I can build this myself.”
NavVis Team
Marketing & ops
Next step
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Questions
Frequent questions about this case study
Code review and test creation consumed senior capacity, while AI tooling was used only sporadically and without a shared standard.
One day facilitated build sprint with the whole engineering org Tool stack setup and prompt standards for every developer Handoff documentation and closing demo with the team
Reviewable adoption across the participating team Code review tool and automated test generation in production A hackathon turned into lived engineering practice
Teams of four to six work best. Overall we run everything from a single team up to several dozen participants.
All three work. On site creates the strongest momentum, remote is leaner logistically, hybrid is the usual compromise for distributed sites.
You get a documented handoff: prototypes, setup, open items and a recommendation on which results deserve to go to production.
We define target metrics before the sprint — hours saved, cycle time, quality or revenue contribution — and review them in the closing session.
Slots are usually available within two to four weeks. With a clearly scoped use case it can be sooner.
Usually not for smaller formats. As soon as production systems are connected, we bring IT and security in early.
There is no certificate at the end, there is a working result: built workflows that keep running in daily operations.