[{"data":1,"prerenderedAt":808},["ShallowReactive",2],{"/en-us/blog/gitlab-premium-with-duo":3,"navigation-en-us":40,"banner-en-us":450,"footer-en-us":460,"blog-post-authors-en-us-David DeSanto, Chief Product Officer, GitLab":701,"blog-related-posts-en-us-gitlab-premium-with-duo":716,"blog-promotions-en-us":745,"next-steps-en-us":798},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":27,"isFeatured":12,"meta":28,"navigation":12,"path":29,"publishedDate":20,"seo":30,"stem":35,"tagSlugs":36,"__hash__":39},"blogPosts/en-us/blog/gitlab-premium-with-duo.yml","Gitlab Premium With Duo",[7],"david-desanto-chief-product-officer-gitlab",null,"product",{"slug":11,"featured":12,"template":13},"gitlab-premium-with-duo",true,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"Unlocking AI for every GitLab Premium and Ultimate customer","GitLab Premium and Ultimate now include GitLab Duo essentials for creating and understanding code throughout the software development lifecycle, all at no additional cost.",[18],"David DeSanto, Chief Product Officer, GitLab","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749660188/Blog/Hero%20Images/blog-premium-with-duo-cover-0756-fy26-v2-1800x945.png","2025-05-15","Today, we launch GitLab 18.0, which highlights our latest innovations and plans in core DevSecOps workflows, security and compliance, and AI. __As part of this release, we're excited to announce that GitLab Premium and Ultimate now include essential GitLab Duo AI capabilities at no additional cost.__ All Premium and Ultimate customers will have immediate access to GitLab Duo Code Suggestions and Chat directly in their preferred supported source code editors and IDEs.\n\n## AI for every development team\n\nArtificial intelligence is now at the center of the developer experience. AI enhances coding in many ways: It analyzes your codebase and provides real-time suggestions as you type, creates functions and methods based on your project's context, reduces repetitive tasks, and automates code reviews.\n\nOver the past few years, we've built [GitLab Duo](https://about.gitlab.com/gitlab-duo-agent-platform/) to infuse generative and agentic AI capabilities like these into our platform. Because writing code is just the start of the software lifecycle – our [global DevSecOps study](https://about.gitlab.com/developer-survey/) found that developers spend 79% of their time on tasks other than code creation – we have adopted a strategy to integrate AI throughout the entire software development lifecycle. \n\nNow, we’re excited to take the next step forward by including essential GitLab Duo capabilities in our GitLab Premium and Ultimate tiers, enabling developers to get the benefits of AI at no additional cost.\n\nBy including GitLab Duo Chat and Duo Code Suggestions in Premium and Ultimate, every software engineer can accelerate their workflow within the IDE — without requiring separate tooling, licensing, or governance. All existing Premium and Ultimate customers now have instant access to Duo Chat and Code Suggestions, once they upgrade to GitLab 18.0, and this enhancement becomes standard for all new customers.\n\n> **\"GitLab has already been instrumental in eliminating our reliance on a fragmented toolchain, which cut costs from disconnected solutions, and streamlined our workflow. Enhancing GitLab Premium with Duo will give us even greater efficiency and cost savings as our developers spend less time on routine coding tasks and more time tackling complex challenges that drive real business value.”**\n>\n>- Andrei Nita, Chief Technology Officer at McKenzie Intelligence Services\n\n\u003Cdiv>\u003Ciframe src=\"https://player.vimeo.com/video/1083723619?badge=0&autopause=0&player_id=0&app_id=58479\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;\" title=\"GitLab Premium with Duo Core\">\u003C/iframe>\u003C/div>\u003Cscript src=\"https://player.vimeo.com/api/player.js\">\u003C/script>\n\n\u003Cbr>\u003C/br>\nPremium and Ultimate customers now have these AI-native capabilities:\n\n#### GitLab Duo Code Suggestions\n\n* Generate complete functions and code blocks from comments  \n* Get intelligent code completions as you type  \n* Support for 20+ programming languages  \n* Available in most popular IDEs\n\nTake this interactive tour to learn about GitLab Duo Code Suggestions (click on the image to start the tour).\n\n\u003Ca href=\"https://gitlab.navattic.com/code-suggestions\">\u003Cimg src=\"https://res.cloudinary.com/about-gitlab-com/image/upload/v1752175911/Blog/b5gdnls7jdyrpeyjby5j.png\" alt=\"GitLab Duo Code Suggestions cover image\">\u003C/a>\n\nLearn more in our [Duo Code Suggestions documentation](https://docs.gitlab.com/user/project/repository/code_suggestions/).\n\n#### GitLab Duo Chat\n\n* Explain unfamiliar code to understand complex functionality  \n* Refactor existing code to improve quality and maintainability  \n* Generate comprehensive test cases to help catch bugs earlier  \n* Fix code issues directly in your workflow\n\n![Duo Chat - API endpoint explanation](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749673912/Blog/Content%20Images/Duo_Chat_-_gif_-_API_endpoint_explanation__3_.gif)\n\nLearn more in our [Duo Chat documentation](https://docs.gitlab.com/user/gitlab_duo_chat/).\n\n> **\"For us, as GitLab users, Duo's intelligent code suggestions have become a daily asset for our developers. Combined with the chat feature, it allows for immediate feedback and iteration, resulting in faster development cycles and a more secure codebase. It's a seamless and powerful addition to our workflows.\"**\n>\n>- Felix Kortmann, Chief Technology Officer, Ignite by FORVIA HELLA\n\n## Duo Enterprise now available to GitLab Premium customers\n\nDue to strong customer demand, we're also excited to share that [GitLab Premium](https://about.gitlab.com/pricing/premium/) customers now can purchase Duo Enterprise, our full suite of AI offerings, without needing to upgrade to GitLab Ultimate. Premium customers can enjoy a rich AI experience seamlessly integrated across the software development lifecycle. This includes exciting GitLab Duo capabilities like:\n\n* [Root Cause Analysis](https://docs.gitlab.com/user/gitlab_duo/use_cases/#root-cause-analysis-use-cases) helps resolve CI/CD pipeline failures quickly, ensuring your CI/CD pipelines remain green.  \n* [Code Review](https://docs.gitlab.com/user/project/merge_requests/duo_in_merge_requests/#have-gitlab-duo-review-your-code) enables faster merge request reviews by leveraging Duo as a code reviewer.  \n* [Advanced Chat](https://docs.gitlab.com/user/gitlab_duo_chat/) summarizes conversations, helps understand code changes, and provides advanced configuration assistance.  \n* [Self-Hosted](https://docs.gitlab.com/administration/gitlab_duo_self_hosted/) enables Duo to be leveraged within air-gapped and offline environments by hosting approved AI models for Duo to use.\n\nIn addition to Duo Enterprise availability, we continue to invest in the success of GitLab Premium customers. Since the launch of GitLab 17, [we’ve shipped more than a hundred features and improvements](https://gitlab.com/gitlab-org/gitlab/-/releases), including: \n\n* [**CI/CD Catalog**](https://about.gitlab.com/blog/ci-cd-catalog-goes-ga-no-more-building-pipelines-from-scratch/) enables developers to share, discover, and reuse   \npre-existing CI/CD components and configurations.  \n* [**Artifact registry**](https://docs.gitlab.com/user/packages/virtual_registry/) gives developers secure access to artifacts and seamless integration with CI/CD pipelines.  \n* [**Remote development**](https://docs.gitlab.com/user/project/remote_development/) enables developers to work in on-demand,  \ncloud-based development environments.\n\n> [Learn more about GitLab Premium features.](https://about.gitlab.com/pricing/premium/#wp-premium-features)\n\n## GitLab Duo: AI that meets organizations where they are\n\nGitLab customers have a comprehensive menu of Duo offerings, across our Pro and Enterprise solutions, to meet you where you are in the AI adoption cycle – the further along your teams are, the more capabilities you can use to build, test, and deploy secure software faster.\n\n![Key features in Duo plans](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749673912/Blog/Content%20Images/Screenshot_2025-05-14_at_8.50.34_AM.png)\n\n## How current GitLab Ultimate and Premium customers can get started with Duo\n\nStarting with GitLab 18.0, for existing Ultimate and Premium customers, Duo Code Suggestions and Chat features will be off by default but can easily be enabled – learn how below.\n\nTo start experiencing GitLab Premium and Ultimate with Duo: \n\n1. Ensure you're on GitLab Premium or Ultimate. If not, you can start a free trial. \n\n2. Enable GitLab Duo in your organization settings.\n\n3. If using a local IDE, install the appropriate GitLab [Editor Extension](https://docs.gitlab.com/editor_extensions/#available-extensions). \n\n4. Start using Code Suggestions and Chat in your preferred supported local IDE or the GitLab Web IDE.\n\n**Note:** For new customers and trials, GitLab's AI capabilities will be enabled automatically.\n\n## AI-native development requires a DevSecOps platform\n\nAI is fundamentally reshaping the developer experience. Organizations won't just have more people building software. They'll have more production-ready code generated by AI – **making GitLab more essential than ever.** \n\nWe built GitLab Premium and Ultimate with Duo specifically for this new reality, giving teams one secure foundation for all their code. As AI generates code across your organization, GitLab becomes your control center: no separate tools for security scanning, compliance checks, or managing pipelines. Just a single, unified platform that scales with your organization and helps ensure all code meets your standards before reaching production. As AI accelerates your development, GitLab enables you to maintain control, security, and quality from end to end.\n\n> To learn more about GitLab Duo and all the ways it can transform how your team works, [visit our GitLab Premium page](https://about.gitlab.com/pricing/premium/) or if you are a GitLab customer, reach out to your GitLab representative to schedule a demo. Finally, we invite you to join us on June 24, 2025, for our [GitLab 18 virtual launch event](https://about.gitlab.com/eighteen/) to learn about the future of AI-native software development.\n",[23,24,25,26,9],"AI/ML","DevSecOps platform","news","features","yml",{},"/en-us/blog/gitlab-premium-with-duo",{"title":15,"description":16,"ogTitle":15,"ogDescription":16,"noIndex":31,"ogImage":19,"ogUrl":32,"ogSiteName":33,"ogType":34,"canonicalUrls":32},false,"https://about.gitlab.com/blog/gitlab-premium-with-duo","https://about.gitlab.com","article","en-us/blog/gitlab-premium-with-duo",[37,38,25,26,9],"aiml","devsecops-platform","VR9duR7nG8APTLhEe8E6M9MU6boXlVqQFhzw7C7kUbA",{"data":41},{"logo":42,"freeTrial":47,"sales":52,"login":57,"items":62,"search":370,"minimal":401,"duo":420,"switchNav":429,"pricingDeployment":440},{"config":43},{"href":44,"dataGaName":45,"dataGaLocation":46},"/","gitlab logo","header",{"text":48,"config":49},"Get free 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statement",{"items":691},[692,695,698],{"text":693,"config":694},"Terms",{"href":520,"dataGaName":521,"dataGaLocation":468},{"text":696,"config":697},"Cookies",{"dataGaName":530,"dataGaLocation":468,"id":531,"isOneTrustButton":12},{"text":699,"config":700},"Privacy",{"href":525,"dataGaName":526,"dataGaLocation":468},[702],{"id":703,"title":704,"body":8,"config":705,"content":707,"description":8,"extension":27,"meta":711,"navigation":12,"path":712,"seo":713,"stem":714,"__hash__":715},"blogAuthors/en-us/blog/authors/david-desanto-chief-product-officer-gitlab.yml","David Desanto Chief Product Officer Gitlab",{"template":706},"BlogAuthor",{"name":18,"config":708},{"headshot":709,"ctfId":710},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749660185/Blog/Author%20Headshots/david-headshot.jpg","david",{},"/en-us/blog/authors/david-desanto-chief-product-officer-gitlab",{},"en-us/blog/authors/david-desanto-chief-product-officer-gitlab","CWNslzhrEbXP6GadZytZo-1T5TW8lGehoUf1Fh5cpMU",[717,729,735],{"content":718,"config":727},{"title":719,"description":720,"authors":721,"heroImage":723,"date":724,"body":725,"category":9,"tags":726},"GitLab 18.11: Budget guardrails for GitLab Credits","Learn how new spending caps and per-user credit limits give organizations the budget guardrails to scale GitLab Duo Agent Platform.",[722],"Bryan Rothwell","https://res.cloudinary.com/about-gitlab-com/image/upload/v1776259080/cakqnwo5ecp255lo8lzo.png","2026-04-16","Teams using GitLab Duo Agent Platform with on-demand GitLab Credits are shipping faster, catching bugs earlier, and automating tasks that used to take entire sprints. But as adoption grows, so does oversight from finance, procurement, and platform teams to prove that AI spending is bounded, predictable, and controllable.\n\nOne of the greatest barriers to broader AI adoption isn't skepticism about the technology. It's uncertainty about managing spend. Without budget caps, a busy month could produce unexpected expenses. Without per-user limits, a handful of power users could burn through the team's credits before the month is over. And without either, engineering leaders who want to expand their use of agentic AI for software development have to jump through more hoops for budget approval.\n\nSince its [general availability](https://about.gitlab.com/blog/gitlab-duo-agent-platform-is-generally-available/), GitLab Duo Agent Platform has provided usage governance and visibility. With GitLab 18.11, we're introducing usage controls for [GitLab Credits](https://about.gitlab.com/blog/introducing-gitlab-credits/): spending caps and budget guardrails that give your organization even more control and transparency over how credits are consumed.\n\n## Managing GitLab Credits\n\nGitLab 18.11 adds three layers of control over GitLab Credits consumption: a subscription-level spending cap, per-user credit limits, and visibility into cap status and enforcement.\n\n### Subscription-level spending cap\n\nBilling account managers can now set a hard monthly ceiling for on-demand GitLab Credits consumption for their entire subscription.\n\nHere's how it works:\n\n* **Set a cap** in the `Customers Portal` under your subscription's GitLab Credits settings.  \n* **Enforce spend limits automatically.**  When on-demand usage reaches the cap, DAP access is paused for all users on that subscription until the next monthly period begins.  \n* **Make adjustments as you go.** Raise or disable the cap mid-month to restore access.\n\nThe cap resets each monthly period and your configured limit carries forward unless you change it. Because usage data is synchronized periodically rather than in real time, a small amount of additional usage may occur after the cap is reached before enforcement takes effect. See the [GitLab Credits documentation](https://docs.gitlab.com/subscriptions/gitlab_credits/) for details.\n\n### User-level spending caps\n\nNot every user consumes credits at the same rate, and that's expected. But when one or two power users account for a disproportionate share of the pool, the rest of the team can lose access before the month is over.\n\nPer-user credit caps prevent any single user from consuming more than their fair share:\n\n* **Flat per-user cap.** Set a uniform credit limit that applies equally to every user on the subscription through the GitLab GraphQL API. Unlike the subscription-level cap, the per-user cap applies to a user's total consumption across all credit sources.  \n* **Custom per-user overrides.** For organizations that need differentiated limits, you can set individual credit caps for specific users through the GraphQL API. For example, you could give your staff engineers a higher allocation while applying a standard limit to the broader team.  \n* **Individual enforcement.** When a user reaches their cap, they retain full access to GitLab. Only their Duo Agent Platform credit usage is paused until the next billing cycle. Everyone else keeps working uninterrupted until they hit their own limit or the subscription-level cap is reached, whichever comes first.\n\n### Visibility and notifications\n\nWhen a subscription-level cap is reached, GitLab sends an email notification to billing account managers so they can take action: raise the cap, wait for the next period, or redistribute credits.\n\nWithin GitLab, group owners (GitLab.com) and instance administrators (Self-Managed) can view which users have been blocked due to reaching their per-user cap and restore access by adjusting the cap through the GraphQL API. \n\n## How budget guardrails help organizations scale AI usage\n\nGuardrails are essential as organizations ramp up their AI adoption. Here's why:\n\n### Predictable AI budgets\n\nUsage controls for GitLab Duo Agent Platform turn AI into a bounded, predictable budget item using on-demand GitLab Credits. That makes it easier to deploy agents across the software development lifecycle and get sign-off from finance, justify renewals, and plan quarterly spend.\n\n### Governance and chargeback\n\nLarge organizations often need to align AI consumption with internal budgets, cost centers, or departmental policies. Per-user caps give platform teams a straightforward mechanism to allocate credits fairly and track consumption at the individual level. The API import options make it practical to manage caps at enterprise scale. Combined with per-user usage data from the GitLab Credits dashboard, organizations can track consumption patterns to inform their own internal chargeback or budget allocation processes.\n\n### Confidence to scale\n\nMany customers start GitLab Duo Agent Platform with a small pilot group. Usage controls remove risks associated with expanding that pilot across the organization. You can roll out Duo Agent Platform to hundreds or thousands of developers knowing there's a hard ceiling protecting your budget. If usage grows faster than expected, you'll hit the cap, not an unexpected invoice.\n\n## Addressing the seat-based and visibility conundrum\n\nMany AI coding tools take a seat-based approach to cost management. You buy a fixed number of seats at a flat per-user price, and that's your budget. It's simple, but rigid. You pay the same whether a developer uses the tool ten times a day or never touches it. And as vendors introduce premium models and usage-based overages on top of seat pricing, the cost predictability that seat-based licensing promised starts to erode.\n\n\nGitLab takes a different approach. Usage-based pricing with hard caps and a single governance dashboard. You get the flexibility of paying for what your teams actually use, with the budget predictability of enforced spending limits.\n\n## Real-world usage controls\n\n**One example is a mid-size SaaS customer that wants to protect their monthly budget.** A 200-person engineering organization sets a subscription-level cap equal to their expected on-demand usage. Their VP of Engineering can confidently tell finance that GitLab Duo Agent Platform spend will never exceed the approved amount, even as they onboard new teams. If they approach the cap mid-month, the billing account manager gets a notification and can decide whether to raise the limit or wait for the next period.\n\n**At GitLab, we also work with large enterprises that want to keep usage fair across teams.** A global financial services company with 2,000 developers uses per-user caps to ensure equitable access. Staff engineers working on complex refactoring projects get a higher individual allocation via API, while most developers receive a standard flat cap. No single user can exhaust the pool, and the platform team uses the per-user usage data in the GitLab Credits dashboard to track consumption patterns and inform quarterly budget planning.\n\n## Getting started\n\nUsage controls are available for both GitLab.com and Self-Managed customers running GitLab 18.11. Different controls are configured in different places depending on the scope and your role.\n\n**Subscription-level cap**\n\nBilling account managers set the subscription-level on-demand cap in the Customers Portal:\n\n1. Sign in to the `Customers Portal`.  \n2. On your subscription card, navigate to **GitLab Credits** settings.  \n3. Enable the monthly on-demand credits cap and enter your desired limit.\n\n**Flat per-user cap**\n\nThe flat per-user cap can be set through the GitLab GraphQL API by namespace owners (GitLab.com) or instance administrators (Self-Managed). Check the [GitLab Credits documentation](https://docs.gitlab.com/subscriptions/gitlab_credits/) for the latest on available configuration surfaces.\n\n**Custom per-user overrides**\n\nFor differentiated limits, namespace owners (GitLab.com) and instance administrators (Self-Managed) can set individual caps programmatically. This is useful for automation and infrastructure-as-code workflows.\n\n**Monitor usage and cap status**\n\n* **Customers Portal:** View detailed usage and cap status.  \n* **GitLab.com:** Group owners can view blocked users under **Settings > GitLab Credits**.  \n* **Self-Managed:** Instance administrators can view cap status and blocked users under **Admin > GitLab Credits**.\n\n## GitLab Duo Agent Platform is ready to scale\n\nUsage controls are available now in GitLab 18.11. If you've been waiting for the right guardrails before expanding GitLab Duo Agent Platform across your organization, this is your moment. Set your caps, roll out Duo Agent Platform to more teams, and start shipping faster!\n\n> [Learn more about GitLab Credits and usage controls](https://docs.gitlab.com/subscriptions/gitlab_credits/).",[9,23,25],{"featured":31,"template":13,"slug":728},"gitlab-18-11-budget-guardrails-for-gitlab-credits",{"content":730,"config":733},{"title":731,"heroImage":723,"description":732,"date":724,"category":9},"GitLab 18.11 release","This release includes Agentic SAST Vulnerability Resolution, Data Analyst Foundational Agent, CI Expert Agent, and more.",{"featured":31,"template":13,"externalUrl":734},"https://docs.gitlab.com/releases/18/gitlab-18-11-released/",{"content":736,"config":743},{"title":737,"description":738,"authors":739,"heroImage":723,"date":724,"body":741,"category":9,"tags":742},"GitLab 18.11: CI Expert and Data Analyst AI agents target development gaps","Set up CI and query your software development lifecycle data with two new GitLab Duo Agent Platform foundational agents available in GitLab 18.11.",[740],"Corinne Dent","AI-generated code moves faster than the systems around it can keep up with. More code means more merge requests queued, more pipelines to configure, more questions about delivery that nobody has time to answer — and most of the tooling teams rely on wasn't built for this pace.\n\nIn GitLab 18.11, two new foundational agents for Duo Agent Platform address specific gaps in the development lifecycle that AI has largely left untouched:\n* CI Expert Agent (now in beta) focuses on the gap between writing code and getting it into a running pipeline\n* Data Analyst Agent (now generally available) focuses on the gap between shipping code and being able to answer basic questions about how that delivery is actually going.\n\n\nThese are problem areas that couldn't be solved by a general-purpose assistant. A tool running outside GitLab can generate a YAML file or answer a question, but it has no awareness of how your pipelines have historically performed, where failures cluster, or what your actual MR cycle times look like. That context lives in GitLab. These agents do too.\n## Fast CI setup with CI Expert Agent\n\nAI has made it easier than ever to write code. Getting that code into a running pipeline is still something most teams do days, or weeks, later — if at all. The blank-page problem isn't in the editor anymore. The blank page is now in `.gitlab-ci.yml`.\n\nDevelopers who have never configured CI don't know what language detection looks like in YAML, what their test commands should be, or how to validate the result before pushing. Teams either copy a config from a previous project that may not fit, stitch together examples from documentation, or wait for the one person who's done it before. If that person isn't available, CI becomes the thing you'll \"get to later.\" Later becomes never.\n\nWhen CI never happens, the impact shows up everywhere else. Changes ship without a reliable safety net, regressions surface in production instead of in pipelines, and work piles up in bigger, riskier batches because no one wants to be the person who “breaks the build.” Over time, teams normalize working in the dark, often relying on undocumented institutional knowledge and ad-hoc testing, instead of having a fast, predictable feedback loop baked into every change.\n\nCI Expert Agent, now available in beta, removes that friction. It inspects your repository, identifies your language and framework, and proposes a working build and test pipeline tailored to what's actually there — then explains every decision in plain language. The target: a running pipeline in minutes, with no YAML written by hand.\n\nWhat CI Expert Agent does:\n\n* Repo-aware pipeline generation detects language, framework, and test setup \n* Generates valid, runnable build and test configurations   \n* Guided first-pipeline flow with plain-language explanation of each step in Agentic Chat  \n* Native GitLab CI semantics with no config translation required\n\nBecause it runs inside GitLab and sees real pipeline behavior over time, each improvement can build on how teams actually work, not just on static examples.\n\u003Ciframe src=\"https://player.vimeo.com/video/1183458036?badge=0&autopause=0&player_id=0&app_id=58479\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;\" title=\"CI/CD Expert Agent\">\u003C/iframe>\u003Cscript src=\"https://player.vimeo.com/api/player.js\">\u003C/script>\n\u003Cbr>\u003C/br>\n\nCI Expert Agent is available on GitLab.com, Self-Managed, Dedicated; Free, Premium, Ultimate Editions with Duo Agent Platform enabled.\n\n## Query GitLab data in plain language with Data Analyst Agent\n\nAI has sped up how teams ship. Answering basic questions about how that work is going has gotten harder, not easier.\n\nHow long are MRs sitting in review? Which pipelines are slowing teams down? Are deployment targets actually being hit? These questions used to be answerable by glancing at a dashboard. Now, with more code, more teams, and more complexity, the data exists — it's in GitLab — but accessing it still means waiting on an analytics team, filing a dashboard request, or learning GLQL.\n\nData Analyst Agent targets that gap. Ask a natural-language question and get an instant visualization in Agentic Chat. No query language, no dashboard request, no waiting for the answers to be assembled by someone else.\n\nFor example, the agent can answer questions about the following topics for these roles:\n\n* Engineering managers: MR cycle time, throughput by project, where reviews get stuck  \n* Developers: Contribution patterns, flaky tests blocking their MRs, pipeline speed trends  \n* DevOps and platform engineers: Pipeline success/failure rates, runner utilization, deployment frequency  \n* Engineering leadership: Cross-portfolio deployment frequency, project health metrics, lead time comparisons\n\nNow generally available in 18.11, the agent covers MRs, issues, projects, pipelines, and jobs — full software development lifecycle coverage, expanded from the beta scope. Because Data Analyst Agent queries what's already in GitLab, the context is always current, and there's no pipeline to maintain or third-party tool to keep synchronized. Generated GitLab Query Language queries can be copied and used anywhere GitLab Flavored Markdown is supported, with direct export to work items and dashboards on the roadmap.\n\n\u003Ciframe src=\"https://player.vimeo.com/video/1183094817?badge=0&autopause=0&player_id=0&app_id=58479\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;\" title=\"Data Analyst agent demo\">\u003C/iframe>\u003Cscript src=\"https://player.vimeo.com/api/player.js\">\u003C/script>\n\u003Cbr>\u003C/br>\n\nData Analyst Agent is available on GitLab.com, Self-Managed, Dedicated; Free, Premium and Ultimate Edition with Duo Agent Platform enabled.\n\n## One platform, connected context\n\nBoth agents run inside GitLab, with access to the code, pipelines, issues, and merge requests already there. That's what separates platform-native AI from a disconnected assistant: the context is always current, and it only gets more useful over time. CI Expert Agent and Data Analyst Agent represent two concrete steps toward a platform where AI doesn't just help you write code faster; it helps you understand, ship, and maintain what gets built.\n\n> [Start a free trial of GitLab Duo Agent Platform](https://about.gitlab.com/gitlab-duo/) to experience these foundational AI agents.",[23,26,9],{"featured":12,"template":13,"slug":744},"ci-expert-and-data-analyst-ai-agents-target-development-gaps",{"promotions":746},[747,761,772,784],{"id":748,"categories":749,"header":751,"text":752,"button":753,"image":758},"ai-modernization",[750],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":754,"config":755},"Get your AI maturity score",{"href":756,"dataGaName":757,"dataGaLocation":244},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":759},{"src":760},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":762,"categories":763,"header":764,"text":752,"button":765,"image":769},"devops-modernization",[9,569],"Are you just managing tools or shipping innovation?",{"text":766,"config":767},"Get your DevOps maturity score",{"href":768,"dataGaName":757,"dataGaLocation":244},"/assessments/devops-modernization-assessment/",{"config":770},{"src":771},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":773,"categories":774,"header":776,"text":752,"button":777,"image":781},"security-modernization",[775],"security","Are you trading speed for security?",{"text":778,"config":779},"Get your security maturity score",{"href":780,"dataGaName":757,"dataGaLocation":244},"/assessments/security-modernization-assessment/",{"config":782},{"src":783},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"id":785,"paths":786,"header":789,"text":790,"button":791,"image":796},"github-azure-migration",[787,788],"migration-from-azure-devops-to-gitlab","integrating-azure-devops-scm-and-gitlab","Is your team ready for GitHub's Azure move?","GitHub is already rebuilding around Azure. Find out what it means for you.",{"text":792,"config":793},"See how GitLab compares to GitHub",{"href":794,"dataGaName":795,"dataGaLocation":244},"/compare/gitlab-vs-github/github-azure-migration/","github azure migration",{"config":797},{"src":771},{"header":799,"blurb":800,"button":801,"secondaryButton":806},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":802,"config":803},"Get your free trial",{"href":804,"dataGaName":51,"dataGaLocation":805},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":506,"config":807},{"href":55,"dataGaName":56,"dataGaLocation":805},1776442971126]