Can AI handle our technical documentation?

Yes. The assistant works with your bills of materials, specifications and existing manuals. It produces drafts in your format that experts approve. That removes the busywork without giving up technical control.

What about CAD and design data?

We build CAD-adjacent assistants for research, standards and material data and connect to metadata from your systems. Actual design stays in your CAD environment, AI takes over lookups and support work.

Do our design and quote data stay secure?

We work in your environment with your accounts. Sensitive design and calculation data stays with you. The hackathon also delivers the documented internal AI literacy measures record for your team.

How big does our team need to be?

The Spark format runs in one day with up to 10 people, Ignite over two days with 10 to 15, Blaze over three to five days from 15 people. Pricing on request in the discovery call.

Industry

AI Workshop for Mechanical Engineering, One Day Onsite

Technical documentation gets rewritten for every variant. Quotes and tenders cost engineers days. Spare parts get searched across scattered catalogs and old drawings. Maintenance logs never get analyzed in a structured way. An AI workshop, one day onsite, builds a live assistant with your team for exactly these tasks. By evening there is a running prototype that makes quotes faster or finds the spare part in seconds, not an official attestation. Need more afterward, you scale straight up into the multi-day Corporathon hackathon, plus the documented competence record under EU AI Act Article 4, mandatory since 2 February 2025.

Real prototypes instead of slides
Facilitated by AI practitioners
Ready to run within a week
Documented handoff included

Book a discovery call See the process

Teilnehmende im Plenum eines KI-Hackathons

Built for

The format

Knowledge turns into a working prototype.

AI workshop for mechanical engineering, one day onsite on documentation, quotes and spare parts. Entry point before the hackathon.

Where industrial teams lose time

What the team builds

Challenges from the plant and engineering. A documentation assistant as a Custom GPT that turns bills of materials and specifications into operating and maintenance texts. A quote pipeline in n8n that reads tenders, extracts line items and fills calculation templates. A spare part search with Claude Code across your catalogs and drawings. A maintenance log analyzer built in Lovable, plus an engineering research assistant for standards and material data.

One week to your hackathon

Want more after the workshop day? You move straight into the multi-day Corporathon hackathon. Here is how that path runs. 1. Intro call, we understand products, production and pain. 2. Tools and challenges call, we pick the automations with the biggest lever. 3. Finalizing data and access, ERP, documentation, catalog data. 4. Preparation, we set up environment and sample data. 5. Hackathon days, tool workshop in the morning, sprint on the prototype, pitches at the end.

Classic training vs. Corporathon

A training shows engineers AI on slides. A hackathon delivers the quote assistant that halves the next tender. That keeps team usage high instead of vanishing after a few weeks.

Output, not slides

A hackathon is not a seminar. It is a facilitated sprint where teams rebuild real work with AI.

0 week

from scope to ready-to-run sprint

0 formats

Spark, Ignite and Blaze

0 steps

from call to documented handoff

How it works

Clear steps from scope to handoff.

Intro call

Corporathon + sponsor · goal, scope and date

Challenge design

Corporathon + team leads · real use cases and tool stack

Data & access

Client · approved data, roles and boundaries

Tool workshop

Corporathon · teams can use the stack

Hackathon sprint

Teams · working prototypes

Next step

Ready for your hackathon?

Book a discovery call directly, we clarify goal, format and date in the call.

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FAQ

Questions that should be clear before the first call.

AI workshop for mechanical engineering, one day onsite on documentation, quotes and spare parts. Entry point before the hackathon.

You decide which data enters the sprint. Access, privacy and boundaries are agreed upfront and we only work with approved material.

You do. Prototypes, automations, workflows, prompts and generated code belong to your company after the sprint.

We work with the stack that fits you: LLM APIs, automation and data platforms, and your existing systems.

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 proof of participation at the end, there is a working result: built workflows that keep running in daily operations.