AI Workshop for Finance and Insurance, One Day Onsite
Finance and insurance teams lose time to processes that are regulated, document heavy and slow. Claims pre-checks that wade through attachments and forms. Compliance and KYC document analysis that ties up specialists. Report automation that needs hands-on work every month. Customer inquiry triage where urgent items drown, and contract summarization that eats time. The AI workshop, one day onsite, starts on exactly one of these tasks, cleanly within data protection and regulation. Your team builds a reviewed prototype in a single day instead of a proof of participation. Need more, you scale straight into the multi-day Corporathon hackathon, with a documented competence record under EU AI Act Art. 4, mandatory since 02 February 2025.
Finance and insurance teams lose time to processes that are regulated, document heavy and slow. Claims pre-checks that wade through attachments and forms. Compliance and KYC document analysis that ties up specialists.
The format
Knowledge turns into a working prototype.
AI workshop for finance and insurance, one day onsite, with data protection in mind. Build a first automation, then scale into the hackathon.
01
Where finance and insurance teams lose time
Finance and insurance teams lose time to processes that are regulated, document heavy and slow. Claims pre-checks that wade through attachments and forms. Compliance and KYC document analysis that ties up specialists. Report automation that needs hands-on work every month. Customer inquiry triage where urgent items drown, and contract summarization that eats time. The AI workshop, one day onsite, starts on exactly one of these tasks, cleanly within data protection and regulation. Your team builds a reviewed
02
What the team builds
Challenges from regulated life. A claims pre-check with Claude Code that reads documents, checks completeness and produces a structured proposal. A KYC document analysis in n8n that matches IDs and evidence against requirements. A report autopilot with Gamma that pulls metrics and builds an update. A customer inquiry triage that sorts by topic and urgency, plus a contract summarizer as a Custom GPT.
03
One week to your hackathon
1. Intro call, we understand function, regulation and pain. 2. Tools and challenges call, we pick the automations with the biggest lever. 3. Finalizing data and access, systems, sample documents, data protection frame. 4. Preparation, we set up environment and anonymized sample data. 5. Hackathon days, tool workshop in the morning, sprint on the prototype, pitches at the end.
04
Classic training vs. Corporathon
A training explains AI and compliance on slides. A hackathon delivers the claims pre-check that relieves your handlers from Monday, built within the regulatory frame. That keeps team usage high instead of fading.
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.
01
Intro call
Corporathon + sponsor · goal, scope and date
02
Challenge design
Corporathon + team leads · real use cases and tool stack
03
Data & access
Client · approved data, roles and boundaries
04
Tool workshop
Corporathon · teams can use the stack
05
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 finance and insurance, one day onsite, with data protection in mind. Build a first automation, then scale into the hackathon.
There is no proof of participation at the end, there is a working result: built workflows that keep running in daily operations.
For teams in marketing, sales, operations, product and IT. Coding skills are not required, the facilitation is built so every team ships a working prototype.
Usually one week: scoping call, use-case selection, access and tool setup. After that the sprint is ready to run.
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.
