GitLab emphasizes transparency, independence, and a developer-first approach in its AI-native DevSecOps platform. Enterprise leaders are concerned about control over development infrastructure and code usage in AI. GitLab addresses these by offering Agent Insights for visibility into agent decision-making and expanded AI model support to prevent vendor lock-in. The GitLab AI Transparency Center details data governance, privacy protections, and ethical AI principles, assuring customers that their data is not used for AI training.GitLab provides flexibility in AI model usage, allowing customers to switch providers within 30 days if practices change. The platform offers deployment choices, including on-premises and various SaaS options, and is cloud-neutral. This flexibility aids compliance with data localization laws and strengthens procurement negotiations by preventing restrictive vendor agreements.Security and compliance are built into GitLab's single platform, integrating features like DAST and fuzz testing natively. A unified compliance center simplifies management of standards, reporting, and frameworks, reducing the complexity of using multiple third-party tools. GitLab maintains a strong connection with its open-source community, allowing for direct customer contributions and feedback through initiatives like the open issue tracker and Healthy Backlog Initiative.Customers retain complete control over their data and how it is processed, with access controls and encryption aligned to regulatory frameworks. GitLab's commitment ensures that customer code and data are never used to train AI models. Ultimately, GitLab offers a clear choice for organizations seeking control, transparency, and innovation without vendor lock-in, enabling sustainable digital transformation.