One control plane for teams and agents

GitLab is the intelligent orchestration platform for DevSecOps. It enables speed with control for agentic software engineering. Software teams and their agents plan, build, secure, and ship on one control plane: unified context, orchestration, security and governance, and execution on GitLab Core, inside your security boundary and under your rules.

GitLab runs four peer pillars on one foundation. Execution and Workflows covers planning, source code management, CI/CD pipelines, registry, and delivery. Security and Governance covers application security, software composition analysis, compliance management, and agent governance. Context and Data covers analytics, value stream visibility, and lifecycle context including Context Graph. Agentic Orchestration covers GitLab Duo Agent Platform: agents, agentic workflows, model choice, and extensibility. Deployment and AI inference options let you choose where GitLab runs and which models power agents.

GitLab adapts to your enterprise guardrails for security, compliance, and deployment. GitLab.com is multi-tenant SaaS with fast setup. Self-Managed runs in your environment on any cloud or on premises, including air-gapped patterns. GitLab Dedicated and GitLab Dedicated for Government provide single-tenant SaaS with data residency and isolation controls. Across deployments you can use GitLab-managed models or self-hosted models, and reshape seats and agent usage with GitLab Flex.

Agentic coding tools, scanners, and business systems can plug into GitLab while GitLab stays the governed control plane. Use APIs, webhooks, integrations, and Model Context Protocol (MCP) so agents and tools share context under your policies. Connect planning, security, observability, and cloud systems, plus agentic coding tools such as Claude Code, Codex, and Cursor. Keep tools your teams trust, or consolidate onto native GitLab capabilities over time, without giving up one policy plane and one source of truth.

GitLab Duo Agent Platform is how GitLab orchestrates agents across the software development lifecycle (SDLC). Foundational, custom, and external agents run flows for planning, coding, review, security, and CI/CD while humans stay above the loop with policy, identity, and audit. It turns coding speed into governed delivery across many developers, projects, and releases.

Intelligent orchestration means your teams set intent and guardrails while agents execute within them. Agents pick up work, pass context across stages, and produce outcomes your policies can verify. Humans and agents share one data model and one audit trail, so handoffs shrink and you get speed with control, not speed with chaos.

AI coding tools make individuals faster, but fragmented software development lifecycle (SDLC) tools leave review, security, and release behind. That is the path to speed with chaos. GitLab closes the AI Accountability Gap with lifecycle context agents can trust, policy-as-code at agent velocity, and full auditability of what agents change. Teams keep preferred coding clients while GitLab certifies work from plan to production.

Coding tools keep one developer in flow. GitLab is the agentic infrastructure where many teams, projects, and releases stay connected so coding speed becomes delivery speed. You get unified context (not RAG over disconnected tools), workflows and flows under your rules, and guardrails that scale with agent output. Cloud and model choice stay with you. Point-tool collections cannot match one data model, one security boundary, and one control plane.

GitLab serves technology leaders and platform owners responsible for modernizing their software delivery lifecycle. This includes CIOs, CTOs, and DevOps leaders who need to create unified experiences for engineering, design, and product teams. GitLab supports everyone involved in software delivery: developers, business analysts, product owners, testers, solution architects, security teams, and operations teams working together across the complete software lifecycle.

Measure value on delivery, risk, and modernization outcomes from one data plane. Use DORA metrics, value stream analytics, security and compliance dashboards, and AI and SDLC trends to see velocity, quality, and posture across teams. A Forrester Consulting Total Economic Impact™ study of GitLab Duo Agent Platform found 400% ROI and $7.5M net present value over three years, with payback in under six months. Modernization assessments and customer results show what consolidation and governed agentic delivery can unlock, so decisions rest on shared lifecycle data instead of tool-by-tool snapshots.