Training course · Lovable · Compliance & Data Protection

Lovable for Compliance and Data Protection Teams

Build web apps from prompts: take Lovable from idea to a working React app with Supabase backend, GitHub sync and deployment.

Duration
1 day (7 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

This course connects Lovable with the everyday processes of Compliance & Data Protection. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

Lovable lets you build web applications simply by describing what you need, with no programming knowledge required. In this course, business users from marketing, sales, HR, operations or product management learn how to turn an idea into a clickable, working application within hours: a landing page for a campaign, an internal tool for logging requests, a simple customer portal or a prototype that helps you pitch an idea convincingly inside your organisation.

The course is hands-on throughout. You work on a small project of your own and learn to state requirements clearly, store data securely, set up logins and publish the result. Just as important is a realistic perspective: which projects you can deliver without IT support, when to involve IT or your data protection officer, and how to hand a successful prototype over to a development team. That way you use Lovable productively without creating shadow IT or security risks.

Compliance and data protection teams must keep track of a growing body of rules, from the GDPR and whistleblower protection to supply chain due diligence and the EU AI Act. Generative AI can structure and accelerate this work: AI assistants summarise new regulations, produce gap analyses against existing policies, support records of processing activities and data protection impact assessments and draft clear training content. Automation helps with data subject requests, contract reviews and vendor risk assessments. At the same time, compliance teams are expected to steer AI use across the organisation: AI policies, risk classification under the AI Act and staff AI literacy obligations. Teams that use AI confidently themselves can advise the business better and design effective governance.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Compliance officers and managers
  • Data protection officers and privacy coordinators
  • Information security officers
  • Governance, risk and compliance staff
  • AI governance leads

Typical challenges we address

  • Tracking numerous new regulations and translating them into internal requirements
  • Keeping records of processing and impact assessments up to date
  • Advising business units quickly and soundly when they introduce new tools
  • Steering organisation-wide AI use in a compliant way

What you will be able to do

  • You describe requirements in a way that lets Lovable generate a usable web application.
  • You create a landing page with a form and publish it on your own.
  • You build an internal tool with login, data storage and roles without any coding.
  • You develop clickable prototypes and use them to align with stakeholders.
  • Use AI for regulatory analysis, data protection documentation and contract reviews.
  • Build AI governance with a policy, a tool inventory and risk classification.
  • Advise business units soundly on GDPR and AI Act requirements for AI use.

Course outline

Module 1 From idea to first draft
  • What Lovable can do and what happens behind the scenes, explained plainly
  • Breaking an idea down into goal, user groups, pages and content
  • Writing your first prompt and judging the result
  • Making small, precise change requests instead of starting from scratch
Module 2 Landing pages and web presence
  • Campaign and event pages with a clear message and call to action
  • Adding images, copy and your corporate design
  • Contact and registration forms that store submissions
  • Checking how pages look on mobile and desktop
Module 3 Internal tools and forms
  • Building input forms, overview lists and simple dashboards
  • Storing data in a database without writing SQL
  • Setting up logins and roles: who may see and change what
  • Spotting typical errors and fixing them with the undo history
Module 4 Customer portals and prototypes
  • Simple portals for customers or partners with a protected area
  • Clickable prototypes for product ideas and stakeholder presentations
  • Collecting feedback and implementing iterations in a focused way
  • Handing a well-documented prototype over to development or IT
Module 5 Publishing, security and ground rules
  • Publishing your app and making it available on your own domain
  • Personal data, GDPR and coordination with IT and data protection
  • Costs, usage limits and realistic effort
  • Recognising when a project belongs in professional developers’ hands
Module 6 Hands-on project: your own solution for Compliance & Data Protection
  • AI tool inventory – An app where business units register the AI tools they use, specify purpose and data types and receive an initial risk classification under the AI Act.
  • Data subject request tracker – An internal tool that logs requests, calculates deadlines, reminds owners and documents progress in an audit-proof way.
  • Vendor check – A questionnaire tool that evaluates new vendors' data protection and security answers and compiles open points for the contract review.
Module 7 Data protection, quality & transfer to daily work
  • Compliance and privacy records often contain sensitive information, such as whistleblower reports that must be kept strictly confidential under whistleblower protection laws and must not be entered into unvetted AI tools. At the same time, Article 4 of the EU AI Act requires organisations to ensure sufficient AI literacy among their staff.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Regulatory gap analysis

An AI assistant summarises new regulations, compares requirements with existing policies and processes and produces a structured list of gaps and actions for expert assessment.

Records of processing and DPIAs

Process descriptions and interviews are turned into draft entries for the record of processing activities and risk analyses for data protection impact assessments, reviewed by the DPO.

Reviewing data processing agreements

AI checks vendors' data processing agreements and privacy documentation for the mandatory content under Article 28 GDPR, third-country transfers and technical measures and flags deviations from the internal standard.

Data subject requests

Automations log access and erasure requests, monitor deadlines and draft responses, while data searches and final approval remain with the responsible staff.

Building AI governance

AI helps draft AI policies, build an inventory of AI systems in use and classify them according to the EU AI Act risk categories as a basis for governance board decisions.

Training and awareness

Policies are turned into clear learning modules, case studies and quizzes on data protection, anti-money laundering, anti-corruption or AI literacy, tailored to target groups across the organisation.

Possible hands-on projects

AI tool inventory

An app where business units register the AI tools they use, specify purpose and data types and receive an initial risk classification under the AI Act.

Data subject request tracker

An internal tool that logs requests, calculates deadlines, reminds owners and documents progress in an audit-proof way.

Vendor check

A questionnaire tool that evaluates new vendors' data protection and security answers and compiles open points for the contract review.

Prerequisites

Confident use of a web browser and standard office software is all you need. No programming knowledge is required. You work in compliance, data protection or information security and are familiar with the basics of the GDPR.

Technical requirements

A laptop with an up-to-date browser, a Lovable account (a paid plan is recommended for intensive use) and free GitHub and Supabase accounts.

Data protection & compliance

Compliance and privacy records often contain sensitive information, such as whistleblower reports that must be kept strictly confidential under whistleblower protection laws and must not be entered into unvetted AI tools. At the same time, Article 4 of the EU AI Act requires organisations to ensure sufficient AI literacy among their staff.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Mon, 23 November 2026 Online Request
  • Fri, 11 December 2026 Bremen Request
  • Tue, 12 January 2027 Online Request
  • Mon, 18 January 2027 Salzburg Request
  • Fri, 5 February 2027 Online Request
  • Tue, 16 February 2027 Kaiserslautern Request

Frequently asked questions

Do I own the code Lovable generates?

Yes. The output is standard React and TypeScript code that you can push to your own repository via the GitHub sync. From there it can be developed, tested and deployed entirely independently of Lovable. In the course we show you how to set this up properly from day one so you avoid any lock-in.

Is Lovable suitable for production applications?

For prototypes, MVPs, internal tools and modest customer-facing apps, yes, provided you review security and the data model carefully. Supabase Row Level Security, secrets handling and the maintainability of a growing codebase all need attention. The course covers exactly which checks make sense before you go live.

How does Lovable differ from Cursor or Claude Code?

Lovable is a browser-based app builder with a fixed stack, built-in hosting and Supabase integration, which makes it ideal for getting started quickly. Cursor and Claude Code work inside any existing codebase and technology. Many teams combine them: start in Lovable, then continue in the editor via GitHub.

What does the EU AI Act actually require of companies?

Since early 2025, certain AI practices have been prohibited and organisations must ensure AI literacy among staff. Further obligations cover transparency and providers and deployers of high-risk systems. In the course we classify typical use cases and work out which governance components your organisation needs.

Can data protection officers use AI themselves?

Yes, for example for contract reviews, draft documentation or training content, provided no unnecessary personal data is processed. The legal assessment remains with you. Hands-on experience with AI also improves your advice to the business, because you can judge opportunities and risks more realistically.

How much does “Lovable for Compliance and Data Protection Teams” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 1 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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