<!--IssueSummary start--> <details> <summary> Everyone can contribute. [Help move this issue forward](https://handbook.gitlab.com/handbook/marketing/developer-relations/contributor-success/community-contributors-workflows/#contributor-links) while earning points, leveling up and collecting rewards. </summary> - [Label this issue](https://contributors.gitlab.com/manage-issue?action=label&projectId=278964&issueIid=594388) </details> <!--IssueSummary end--> ## Customer Use Cases - Orbit / GKG This issue is for anyone at GitLab, especially field team members, who wants to understand what's resonating with customers about Orbit / GKG. We're gathering high-impact use cases directly from customer conversations. Use these as inspiration when talking to prospects and customers. --- ### Large enterprise insurance company, self-managed GitLab (migrating to AWS/Kubernetes) **Date:** 2026-02-04 **Deployment:** Self-managed **Interest level:** Strong interest **Use cases that resonated:** - Multi-repo organizational intelligence across a large polyglot codebase (Java, COBOL, Python, Go, Rust, proprietary languages) - Cloud and infrastructure migration assistance - Engineering efficiency measurement with exec-reportable outcomes - Language-to-language translation for legacy/proprietary codebases **What they want:** Very large engineering org wants to understand delivery holistically - where time is spent, where to invest, how to quantify AI value in exec-reportable terms. Deep interest in multi-repo inference and org-level intelligence. Large audience including senior AI leadership with detailed technical engagement on architecture, schema, and language support. **Key requirements / blockers:** - Language support for COBOL, proprietary/internal languages - Temporal graphs (current-state-only indexing is a gap) - Data retention policy clarity - Eval methodology and observability - Clear ROI measurement framework --- ### Large real estate technology company, self-managed GitLab, building an internal developer portal and agentic engineering platform **Date:** 2026-03-20 **Deployment:** Self-managed (Q2 target - will wait) **Interest level:** Strong interest **Use cases that resonated:** - Correlation ID mapping across 9 microservices - discover which repos need changes without cloning all locally - Pipeline inheritance graph - 15,000+ pipelines, map inheritance to find and deprecate old/unsupported pipelines - AMI version discovery - find all Terraform/Packer projects deployed on a specific AMI version across the org - Repo hygiene and agent-readiness scoring - surface repos with bad settings, stale/unowned repos, SOX compliance drift - Agentic code review with GKG context **What they want:** "Our goal is to build agent-ready codebases and a background agents platform. We want to run the agent loop ourselves and need context assembly tools that work as agents-as-tools for fine-grained, pinpointed context. Orbit is the missing piece for structured SDLC context at scale. We want to dogfood this on our own complex systems first and use those as demo use cases for the rest of the org." **Key requirements / blockers:** - ClickHouse procurement friction (Databricks is their data lake; prefer Helm chart deployment without a separate ClickHouse vendor agreement) - Self-managed deployment not yet available (Q2 target) - Swift language support not yet available (mobile team) - Agent identity/IAM: principle-of-least-privilege per agent per task, self-service - Full telemetry and trajectory data for evals and observability (hard requirement - black-box agents are a non-starter) - MCP tool call documentation --- ### Large enterprise investment management firm, self-managed GitLab **Date:** Unknown **Deployment:** Self-managed **Interest level:** Strong interest / trialing **Use cases that resonated:** - Cross-repo knowledge graph for agentic development workflows - Code indexing at scale for structured reasoning over large codebases - Improving context quality for agentic solutions **What they want:** "We're focused on agentic development and evaluating knowledge graphs to shift work paradigms. Goal is to improve search and understanding for agentic solutions. We want to trial the self-installed knowledge graph as soon as it's available for self-managed." **Key requirements / blockers:** - RBAC across repositories (critical, non-negotiable requirement) - Multi-instance support (spanning KG across two separate GitLab instances - not supported today) - Pricing and licensing for self-hosted models - Self-managed service version (targeted early next year per current roadmap) --- ### Mid-market financial services firm (real estate investment), SaaS GitLab **Date:** Unknown **Deployment:** .com **Interest level:** Strong interest - purchase decision imminent **Use cases that resonated:** - Disaster recovery: map all interconnected services and components for migration planning - Vulnerability tracing across repos - Pipeline failure resolution - New developer onboarding in large monorepos - Automated AI context standardization across teams and projects **What they want:** "We want to automate and standardize AI context configuration across all projects for cross-team consistency. The disaster recovery use case is huge for us - using GKG to map all interconnected services and components before migrating infrastructure." Purchase decision pending pricing and professional services details. **Key requirements / blockers:** - Pricing and professional services scope (blocking purchase decision) - SOX compliance support - Project initialization automation for cross-team AI context consistency --- ### Mid-market hardware security company, evaluating airgapped self-managed deployment **Date:** Unknown **Deployment:** Airgapped self-managed **Interest level:** Evaluating **Use cases that resonated:** - Code indexing across repos, issues, and epics for project understanding - Implicit dependency detection (e.g., JSON config changes across services) - Token consumption reduction for AI queries **What they want:** "We want to evaluate GKG on .com first before committing to an airgapped install. C and embedded code is our primary language - that needs to work before we can move forward." **Key requirements / blockers:** - C/embedded code language support (hard blocker - not yet available) - Airgapped deployment path - Full API/MCP access (concern about current limitations) --- ### Large enterprise apparel retailer, SaaS GitLab, experimenting with multiple AI coding tools **Date:** Unknown **Deployment:** .com **Interest level:** Curious **Use cases that resonated:** - New developer onboarding, vulnerability understanding, downstream impact mapping (shown as part of roadmap review) - Jira integration with GKG for cross-platform workflows (Q3 roadmap) **What they want:** Interested in how Orbit fits into the broader AI developer tooling picture alongside competing tools they're already evaluating. Jira integration is a key dependency for adoption. **Key requirements / blockers:** - Jira integration (Q3 planned) - AI governance and credit controls across tools --- ### Large enterprise ERP software vendor, self-managed GitLab **Date:** Unknown **Deployment:** Self-managed **Interest level:** Not interested (explicit feedback) **Use cases that resonated:** None. Customer evaluated GKG and does not find it useful for their current use case. **What they want:** N/A - explicit negative feedback. **Key requirements / blockers:** - Feedback: "lacks full API access; not a full MCP as expected" - Legacy license restrictions blocking AI feature access - Security requirement prohibiting data being sent back to GitLab