AI DPO: Lovable

Hi! This is Assenteo's AI DPO, providing data protection reviews of AI startups to showcase best practices. In these reviews, we assess basic compliance and transparency signals from public sources.

Lovable has been the talk of the tech community since launching earlier this year, whether for the speed of its custom UX or the company’s rapid growth - honestly, impressive.

As non-technical, literature-educated individuals, Assenteo is a big fan of non-technical tools, and we’re particularly excited by developments in this space over the past few months.

But enough about us. Here’s a privacy-first look at Lovable to celebrate what’s working and suggest easy wins to build even more trust.

I) How We Review Companies

Through AI DPO, we’re here to help AI companies build data protection practices that are both compliant and customer-friendly.

When we review a company, we follow three simple principles:

1. We stick to what’s public: Our reviews focus only on public-facing privacy practices, not private strategies, product features, or confidential details (those deeper insights are reserved for Assenteo users).

2. We’re here to raise the bar, not rank companies: Our goal isn’t to criticize. It’s to lift the overall standard of data protection across the AI space and help everyone build stronger, more trusted products.

3. We’re a snapshot in time: Our reviews reflect what we see on the date we publish. Companies change and grow, and so will their privacy practices.

We believe good data protection is good business and we’re excited to be part of helping AI companies get it right.

1. Assenteo’s Take

Lovable is a prompt-based software development tool used by 30,000 paying users, with 25,000 new apps created each day. In this industry, privacy remains crucial to protect both the end user and the builder:

• End user: The personal data inputted into the finished product must be transparently and securely collected and processed.

• Builder: The generated code for created products should facilitate data flows that respect user privacy.

We won’t comment on security assessments in this review, but Lovable has launched a feature to scan for vulnerabilities before launch. This comes in response to some products built with Lovable’s tool having code that previously allowed for poor security practices.

As a young company, Lovable is doing a good job. They are meeting most expectations for a data-compliant business in managing their own operations. However, we’ve identified areas for growth in facilitating privacy protections for end users of generated software and provide further clarity around their own data flows.

2. AI DPO Assessment

Category	Assessment	Notes
Privacy Policy	✅	Lovable hosts a privacy notice for the personal data collection of their builders, available in Lovable's Privacy Policy. This policy was last updated in December 2024.
Data Collection	✅	The Privacy Policy clearly lists the data categories collected: account information, service usage data, and automatically collected information (such as IP address and device info). In terms of transparently sharing what data is collected, the current policies meet expectations.
Data Processing	⚠️	Data sharing with third-party service providers is disclosed. However, specifics about which companies and storage geographical locations are not provided.
User Controls	✅	Users are informed of their GDPR rights (access, correction, deletion, opt-out, and withdrawal). An email address is provided for rights requests.
AI-Specific Disclosures	⚠️	Model training use is disclosed in the Terms. For non-paid users, collected information is used to train models. Opting out of data sharing for model training appears to require becoming a paid user. Lovable describes that user data is used to improve their AI systems, enhance the product, and resolve technical issues. However, it is unclear exactly what data is used, and whether personal data is included.
Cookie Handling	⚠️	Lovable tracks website and app users with standard analytic tools. There is no notice or cookie opt on the website and the Privacy Policy refers to the user’s browsing settings. While you do agree to their Terms and Privacy Policy when you create an account to use the product, this is pre-ticked for users. Practically this means users are not explicitly confirming they have seen the legal documents or explicitly consenting to tracking when they sign up.

Lovable currently stands at: 👌 Level 1 - public basics are in place

3. Highlights

• Consideration of data usage: With the rise of vibe coding, Lovable demonstrates a stronger commitment to data protection than might be expected. They have clearly thought through issues such as data ownership, usage, and access, as reflected in their Privacy Policy and Terms.

• Structure in legal docs: We particularly liked that Lovable avoided making the Privacy Policy overly lengthy by linking to the Terms for further detail.

• Transparency on data use: Additionally, Lovable is transparent about the categories of data they collect and process, and how data is used for LLM training on non-paid plans.

4. Where Trust Can Grow

• Clarify data used for model training: There’s an opportunity to strengthen user trust by clearly explaining what user data is used for model training, especially whether it includes personal data.

• Enhance accessibility and design of policies: It took a bit of effort to locate all the relevant information for this analysis. Applying more thoughtful design and making key data practices more visible could help build user confidence.

• Emphasize proprietary protections: Important information about users’ ownership of generated code is buried in the Terms (mentioned three, yes three, separate times). Bringing this messaging more front and center could strengthen Lovable’s appeal as they grow their enterprise client base.

At Assenteo, we help AI builders turn data protection into a product strength through providing data protection professional services. While this review focused on basic compliance and public transparency, our core service supports full compliance, strong UX practices, and competitive advantage through trust. If you're a serious builder, let's chat.