Do our employees need to know how to code?

No. Modern AI tools let non-technical people build real, working things. We coach every team through the process.

What happens to our company data?

Your data stays yours. We agree on handling and access before the event and work inside your environment wherever possible.

How fast can we run a hackathon?

From our first call to a prototype your team built with AI: one week. The event itself runs for one to five days.

What does a team walk away with?

Working prototypes on your real data, an impact report, a skills library and a clean handover package for IT.

Does this support EU AI Act literacy?

The format builds and documents practical, context-specific competence. Your company remains responsible for assessing its overall Article 4 program.

How many people can take part?

Formats run from a single team of six up to company-wide groups split into parallel teams, each with its own challenge and coach.

Which tools do you work with?

The stack is chosen around your setup: ChatGPT, Claude, Gemini, Copilot, n8n, Make, Zapier, Lovable and your existing CRM or data tools.

Do we need to prepare use cases in advance?

We collect and sharpen the challenges together in the tools and challenges call, so day one starts with building instead of brainstorming.

What happens after the hackathon?

You get a handover package, internal champions who can train their own sub-teams, and an optional follow-up sprint to harden the best prototypes.

Can you run it remotely or on site?

Both. On site works best for energy and momentum; remote and hybrid setups run with the same structure, coaching and pitch format.

AI tool directory

The AI tool stack we build with

Every tool our teams use in company hackathons — assistants, builders, automation platforms and revenue systems. Compare them, then decide what belongs in your stack.

OpenAI ChatGPT

General-purpose AI assistant for every team

ChatGPT is the default entry point for company-wide AI usage. Teams use it for drafting, analysis, research and structured reasoning, and enterprise workspaces add shared prompts, custom GPTs and admin controls.

Claude

Long-context assistant for documents and analysis

Claude handles long documents, policies and codebases with careful reasoning. It is the tool of choice when teams need reliable summaries of contracts, reports or specifications.

Claude Code

Agentic coding in the terminal

Claude Code turns a repository into a workspace an agent can navigate, edit and test. Technical teams use it to automate refactors, scripts and internal tooling.

OpenAI Codex

Cloud coding agent for parallel tasks

Codex runs coding tasks in isolated cloud environments, so several changes can be prepared in parallel and reviewed as pull requests.

Gemini

Multimodal AI inside Google Workspace

Gemini brings AI directly into Docs, Sheets, Gmail and Meet, which makes it the fastest option for organisations already living in Google Workspace.

Microsoft Copilot

AI layer across Microsoft 365

Copilot works inside Teams, Outlook, Word and Excel with the permissions your organisation already uses, which keeps governance simple for regulated companies.

Microsoft 365

The workplace suite AI plugs into

Microsoft 365 is where most enterprise knowledge already lives. Its structure — SharePoint, Teams, Outlook — determines how good any company assistant can become.

Lovable

Ship internal web apps by describing them

Lovable turns a description into a working web application with database, auth and deployment. It is the fastest path from hackathon idea to something colleagues can actually click.

n8n

Self-hostable workflow automation with AI nodes

n8n connects internal systems with AI steps in visual workflows and can run on your own infrastructure, which is often the deciding factor in Europe.

Make

Visual automation for business teams

Make gives non-developers a visual canvas for multi-step automations across SaaS tools, with AI modules for classification, extraction and drafting.

Zapier

The widest integration network

Zapier is the pragmatic choice when a workflow needs to touch a long tail of tools. Its AI actions and agents cover most simple orchestration needs.

Clay

AI research and enrichment in a spreadsheet

Clay chains data providers and AI research steps in a table interface, so revenue teams can build enrichment and scoring logic without engineering support.

Airtable

Structured data layer for AI workflows

Airtable stores the structured records AI workflows read and write, which makes it a common backbone for hackathon prototypes that need to survive the week after.

HubSpot

CRM with native AI across marketing and sales

HubSpot combines CRM, marketing and service data in one place, and its AI features work best when that data is already clean and consistently used.

Salesforce

Enterprise CRM with agent platform

Salesforce is the system of record for large revenue organisations and increasingly the place where AI agents act on that record directly.

Microsoft Dynamics 365

ERP and CRM with Copilot built in

Dynamics 365 covers sales, service and operations for companies already standardised on Microsoft, with Copilot reaching across those modules.

Pipedrive

Lightweight sales CRM with AI assistant

Pipedrive keeps pipeline management simple, which suits smaller sales teams that want AI suggestions without a platform migration.

Attio

Flexible, data-native CRM

Attio models your actual go-to-market objects instead of forcing a standard schema, which makes AI-driven workflows easier to shape around real processes.

Instantly

Cold email infrastructure at scale

Instantly handles inbox rotation, warmup and deliverability for outbound programmes, with AI assistance for sequences and reply handling.

lemlist

Multichannel outreach with personalisation

lemlist combines email, LinkedIn and calls in one sequence and uses AI to adapt messaging per persona rather than per contact gimmick.

Not sure which tools fit your team?

We map your stack in the first hour of every hackathon.

Start Company Hackathon

Client voices

What teams say after the week

Short feedback from hackathons with engineering, marketing, operations and leadership teams.

Our engineers built a code-review assistant in two days that the whole team still uses. No training ever did that.

Engineering leadNavVis

The whole agency was building. Marketers with zero coding background shipped content pipelines that saved real hours.

Managing directorYOYABA

Procurement workflows that used to sit on a roadmap were prototyped and demoed inside the same week.

Head of operationsOnventis

Our leadership cohort left with five working agents and a completely different sense of what AI can do for us.

Programme ownerAdobe cohort

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