Agentic AI, enterprise control: Self-hosted Duo Agent Platform and BYOM

For organizations in regulated industries, the path to AI-powered automation comes with hard constraints. Data residency, vendor control, and governance aren't negotiable, and many organizations have already made significant investments in their own models with rigorous approval processes governing how and where those models operate.With GitLab 18.9, we are delivering two capabilities that close a critical strategic gap for these enterprise customers, transforming GitLab Duo Agent Platform into a deployment-ready, governable AI control plane for the strictest regulatory environments.GitLab Duo Agent Platform Self-Hosted for Online Cloud LicensesWith GitLab Duo Agent Platform, engineering teams create AI-powered flows that automate sequences of tasks, from refactoring services and hardening CI/CD pipelines to triaging vulnerabilities. To date, using GitLab Duo Agent Platform in production with self-hosted models was primarily aligned with offline or add-on licensing paths, not designed for online cloud license customers operating under strict regulations.Now generally available, Self-Hosted for Online Cloud Licenses introduces a usage-based billing model powered by GitLab Credits. This approach provides the transparent and predictable metering that enterprises require for trust and internal chargeback.Data residency and control: You can now run GitLab Duo Agent Platform in production on online cloud licenses while using models you host on your own infrastructure or approved cloud environments. This gives you control over where models run and how inference traffic is routed within your approved environments.Cost transparency and chargeback: Gain granular cost transparency through GitLab Credits and per-request metering, which is essential for accurate internal chargeback and meeting regulatory reporting standards.Adoption acceleration: Removes a significant deployment blocker for adopting agentic AI in sectors like financial services, government, and critical infrastructure, where routing data through external AI vendors is simply not an option.
GitLab 18.9 makes Duo Agent Platform a first-class deployment for online cloud licenses.Bring Your Own ModelSelf-hosting the orchestration layer is only half the story. Many regulated customers have already invested heavily in their own models: domain-tuned LLMs, in-region or air-gapped deployments for data sovereignty, and closed-source, internal models built for their specific risk posture.Bring Your Own Model extends the flexibility of GitLab Duo Agent Platform, allowing administrators to connect third-party or self-hosted models via the GitLab AI Gateway. This ensures customers retain model choice and control.Integration and governance: BYOM models appear alongside GitLab-managed models within GitLab’s AI control plane, allowing Duo Agent Platform to treat them as enterprise-ready options.Granular mapping: Once registered through the AI Gateway, models can be mapped to specific Duo Agent Platform flows or features, giving you fine-grained control over which agents and flows use which models.
Admins maintain responsibility for model validation, performance, and risk evaluation. You own compatibility, performance, and risk evaluation for the models you bring.Together, these capabilities give enterprise engineering leaders comprehensive control over agentic AI. The result is a single, governed control plane for agentic AI, replacing the fragmented mix of point solutions and unmanaged AI tools that many engineering organizations rely on today. It's the combination regulated organizations have been asking for: model freedom plus strong governance, inside the same DevSecOps platform you already trust.Want to try GitLab Duo Agent Platform? Contact us or sign up for a free trial today.This blog post contains "forward‑looking statements" within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934. Although we believe that the expectations reflected in these statements are reasonable, they are subject to known and unknown risks, uncertainties, assumptions and other factors that may cause actual results or outcomes to differ materially. Further information on these risks and other factors is included under the caption "Risk Factors" in our filings with the SEC. We do not undertake any obligation to update or revise these statements after the date of this blog post, except as required by law.

Source: https://about.gitlab.com/blog/agentic-ai-enterprise-control-self-hosted-duo-agent-platform-and-byom/