Babbel

Babbel, a leading subscription-based language learning platform serving 16M+ users worldwide, needed to standardize code quality across their extensive engineering organization. With hundreds of developers working across multiple GitHub organizations, they faced significant challenges in maintaining consistent standards. By implementing DeepSource, they transformed their development practices — successfully rolling out comprehensive code analysis across their entire codebase within just six weeks, while processing thousands of commits monthly.

About Babbel

Founded in 2007 in Berlin, Babbel has grown into one of the world's top language learning platforms, offering interactive courses in 14 languages through web and mobile applications. Their engineering organization, consisting of approximately hundreds of developers across multiple teams, maintains a complex, multi-language technology stack that powers their subscription-based platform, serving millions of users globally with features like bite-sized lessons, live classes, and practical review systems.

The Challenge

For Babbel, maintaining code quality while moving fast is crucial — their platform delivers language learning experiences to millions of users worldwide, processing thousands of interactions daily. As a rapidly growing edtech company, they faced significant challenges in maintaining consistent code quality:

We had no static code analysis per se because we have a lot of teams across multiple organizations. Different teams would have their own linters and local setups in place. There was no way to see the larger picture.

The key challenges included:

• Fragmented Quality Controls: Each team maintained their own linters and local setups
• Inconsistent Standards: Polyglot tech stack with multiple languages and infrastructure code
• Limited Visibility: No unified way to identify gaps or prioritize improvements
• Tool Limitations: Previous solutions saw limited adoption due to noise issues and complexity
• Complex Organization: Multiple GitHub organizations with shared developers across repositories

Why DeepSource

After evaluating several enterprise-grade solutions, Babbel chose DeepSource for several compelling reasons:

1. Comprehensive Language Support: DeepSource's ability to analyze their entire tech stack was crucial for standardization efforts
2. Ease of Use: The platform's well-designed user experience and simple setup process facilitated rapid adoption
3. Accurate Analysis: Significantly lower false positives compared to traditional solutions
4. Cost-Effectiveness: Better value proposition for large-scale deployments

Implementation and Results

Babbel took a strategic approach to implementing DeepSource across their organization:

Rapid Deployment

Within just six weeks, Babbel achieved comprehensive coverage of their codebase while maintaining high developer engagement across teams.

Strategic Rollout

The implementation strategy focused on gradual adoption:

The biggest selling point was saying that we're adding this tool to provide more information—we're not stopping you from doing anything you've been doing. That comes later, but the tool is already there.

Developer Experience

The implementation received enthusiastic responses from developers:

• Teams embraced the IDE extensions for local analysis
• Development groups without established linting began actively using DeepSource's capabilities
• Engineers appreciated the automated fix suggestions for efficient issue resolution

Measurable Impact

Within the first two months:

• Successfully analyzed thousands of commits across the entire codebase
• Enabled standardized quality checks across 7 different programming languages
• Initiated organization-wide conversations about code standards
• Supported shift-left testing initiatives by identifying coverage gaps
• Achieved rapid developer adoption across global teams without mandating usage

Cultural Impact

DeepSource's implementation catalyzed important organizational changes:

We already started having conversations about shared standards, which is great because that's what we want to have in the end. DeepSource aids that by being there and being one of the tools in the chain.

The platform helped:

• Initiate conversations about shared coding standards
• Establish consistent quality baselines across teams
• Support the shift-left testing initiative
• Enable better visibility into code quality across repositories

One of the initiatives I've been driving is shift-left — minimizing manual QA and relying more on tooling and automation. DeepSource isn't just a tool for us; it's a catalyst for cultural change in how we approach code quality.

Babbel's success demonstrates how intelligent tooling can transform engineering culture at scale — enabling global development teams to maintain high quality standards while shipping educational experiences to millions of users worldwide.