The AI Productivity Platform For Engineering Teams
Deliver software with speed, guardrails, intelligence and insights.
Layer 07 · The Brain
GKS
The Garth Knowledge Service: the shared brain every product above is grounded on.
Deliver software with speed, guardrails, intelligence and insights.
Trusted by engineering teams at
The shift from SDLC to ADLC, the AI-assisted Development Lifecycle, created new delivery challenges.
Garth is built for the ADLC, the AI-assisted Development Lifecycle your team is already running.
Products work cohesively to improve productivity.
AI adoption, token spend vs. lines shipped, tool ROI, and optimization signals provide the view leaders need to effectively manage the AI era.
Reviews code against your full repository graph, team guardrails, and inter-PR collision risks, not just the diff in front of it.
Continuous scanning surfaces issues to developers before they become downstream risks or incident reports.
Committed vs landed vs verified. GRelease joins Jira commitment, Git landing, CI verification, and dependency state into one honest read: is this release really on track, or does it only look on track in Jira?
AI assistance in Teams and Slack helps answer technical questions. Detect and remove friction across developer workflows eliminating context switching.
Catch defects and compliance issues before you commit or raise a PR, shifting issues left in the IDE. Identify bugs, security vulnerabilities, and compliance risks proactively.
Garth Universe configures tenancies, licenses, and access integrations across the entire suite.
The Garth Knowledge Service: the shared brain every product is grounded on. A repository graph and shared org context that grounds the entire suite from a single source of truth.
Agents never touch your systems directly. Everything reads through GKS, the governed boundary you control, and every action writes back only through your keys.
GKS ingests only the sources you authorize. Nothing you have not connected ever enters.
Each agent gets the exact data required to do its work, filtered at intake, and nothing beyond it.
Agents read from GKS, never your host systems. Misuse stops at the boundary, not inside your stack.
When an agent writes back to a system, it goes through credentials you provision, scope, and revoke at will.
No rip-and-replace. Garth connects to the tools your teams already use.
Built to connect with your full engineering ecosystem.
Secure access across your identity providers.
Automated onboarding and management.
Data integration across your full tech stack.
On-premise, cloud, or hybrid. Your data stays where it needs to.
Customizable backfill and compliance controls.
Proactive threat detection and response.
Early signals from the teams putting Garth to work across review, delivery, and release.
We're still early with GRelease, but I can already see it fixing the thing that keeps me up at night: knowing whether a release is genuinely safe to ship. My team and I finally have one honest view of release readiness instead of a dozen Slack threads and a gut feeling.
For the first time I can see delivery, quality, and AI spend across every team in one place. G360 turned a quarterly guessing game into a conversation I can actually back with data.
What sold me was that GReview understands the code, not just the diff. It holds every pull request to the same standards we have been trying to enforce by hand for years, and it does not get tired at 6pm on a Friday.
Our sprints used to end in surprises. With G360 I can watch risk building up mid-cycle instead of finding out at the retro. Predictability went from a hope to a habit.
GReview took the review bottleneck off my leads. It governs every PR before a human ever opens it, so we spend our time on design decisions instead of catching the same issues over and over.
As the volume of AI-generated code exploded, review became the wall we kept hitting. GReview flags the risky changes early and lets the clean ones through, so my PRs move in hours, not days.
| Capability | Garth Suite | CodeRabbit | Greptile | LinearB | Hivel |
|---|---|---|---|---|---|
| AST + GKS-grounded code review | ✓ GReview | ◐ | ◐ | ✗ | ✗ |
| Inter-PR collision detection | ✓ GReview | ✗ | ✗ | ✗ | ✗ |
| Team guardrail enforcement | ✓ GReview | ◐ | ◐ | ✗ | ✗ |
| Hidden agentic risk detection | ✓ GReview | ✗ | ✗ | ✗ | ✗ |
| Automated test generation for PRs | ◐ Roadmap | ✗ | ✓ TREX | ✗ | ✗ |
| Prompt Valuation | ◐ Roadmap | ✗ | ✗ | ✗ | ✗ |
| Multi-VCS (GitHub + GitLab + Bitbucket + Azure DevOps) | ✓ All 4 | ✓ GH+GL | ◐ GH+GL | ✓ All 4 | ✓ |
| Repo security scanning | ✓ GScan | ✗ | ✗ | ✗ | ✗ |
| Developer agent (Slack + Teams) | ✓ GAssist | ◐ | ✗ | ◐ WorkerB | ◐ Slack |
| IDE: VS Code + AI-native editors | ✓ G-IDE | ✗ | ◐ | ✗ | ✗ |
| Lines-changed vs. tokens-used analytics | ✓ G360™ | ✗ | ✗ | ◐ Copilot ROI | ◐ Adoption |
| DORA delivery metrics | ✓ G360™ | ✗ | ✗ | ✓ | ✓ |
| CI/CD pipeline analytics | ✓ G360™ | ✗ | ✗ | ✓ | ◐ |
| Release readiness: committed vs landed vs verified | ✓ GRelease | ✗ | ✗ | ◐ | ✗ |
| Cross-signal release reconciliation (Jira · Git · CI · deps) | ✓ GRelease | ✗ | ✗ | ✗ | ✗ |
| Cloud cost & ROI (AWS · GCP · Azure) | ✓ G360™ | ✗ | ✗ | ◐ | ✗ |
| AI leader identification | ✓ G360™ | ✗ | ✗ | ✗ | ✗ |
| Cross-tool shelfware detection | ✓ G360™ | ✗ | ✗ | ✗ | ✗ |
| Graph-based knowledge retrieval | ✓ GKS | ✗ | ◐ | ✗ | ✗ |
| Central control plane + licensing | ✓ Universe | ✗ | ✗ | ◐ | ◐ |
Garth doesn't write your code. Claude Code, Codex, and other AI coding agents do that. Garth governs, secures, and measures everything that happens after the prompt: the review, the risk, the delivery, the spend.
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