Keep your quality gates. Add supply chain security, AI triage and fixes that arrive as pull requests, on the same code.
See how Xygeni compares to SonarQube on your own repositories.
What sets us apart
MEW flags malicious packages before a signature exists, across packages, containers, pipelines and commits.
AI triages every finding (true or false positive, urgency and effort) and ranks what is reachable and exploitable.
Cross-tool ASPM, AI inventory and security-first remediation, over your own findings and third-party ones.
Use your own model provider. Your code never leaves your infrastructure, on-prem or air-gapped.
Code quality
Code smells, complexity, maintainability, dead code, duplication and naming, measured the same way in every language you run, so results are comparable across teams.
Baseline-aware quality gates on pull requests block what a PR introduces, not the debt you inherited. Enforceable from day one, even on legacy code.
AI Remediation proposes the change and opens the pull request. Every finding is ranked by remediation complexity, with estimated effort saved.
Quality findings sit in the same prioritization funnel as security findings. The file with the worst maintainability score is often the one with the injection flaw.
From noise to action
Xygeni narrows thousands of alerts to the few that are real, reachable and exploitable. Then it fixes them.
Side by side
| Capability |  | SonarQube |
|---|---|---|
| Code quality analysis (smells, complexity, duplication, dead code) | One consistent standard across languages | Yes |
| Baseline-aware quality gates on pull requests | Yes | Yes |
| AI fixes for quality findings delivered as pull requests | Opens the PR | Suggestions only, no pull request. |
| Quality and security in one prioritization funnel | Unified | Separate issue lists |
| Malware across the SDLC + endpoint (Shield) | Packages, containers, pipelines and commits. | Known malicious packages, in CI. |
| AI triage: true / false-positive verification | Yes | No |
| Noise-cutting prioritization (attack-path funnel) | Reachable + exploitable | Severity-based |
| Automated remediation: SAST, SCA & secrets (breaking-change aware) | Yes | AI fix suggestions, no pull request, no breaking-change analysis. |
| Remediation Risk: which callers a fix breaks, at method level | Method + call sites identified | No impact analysis |
| Developer endpoint protection | Packages, IDE extensions and plugins, plus network traffic, under one org policy. | Not available |
| Dynamic testing (DAST) | Yes | No |
| Cross-tool ASPM (ingest 3rd-party findings) | Yes | No |
| AI Security: discover, detect & enforce (AI-BOM) | Yes | No |
| Bring-your-own-LLM · code stays in your infra | Yes | Azure OpenAI only (Server) |
| Behavioral anomaly detection (SCM & CI) | Yes | No |
Competitor information is based on publicly available documentation, reviewed September 2026. Spotted something out of date? Let us know.
Secure the AI
Live inventory of every model, dataset, agent and MCP server, with an audit-ready AI-BOM mapped to the EU AI Act.
Deterministic + LLM detection of prompt injection, insecure MCP and data exposure, aligned to OWASP, applied to third-party findings too.
Shield protects the developer endpoint: age-based install control for packages, IDE extensions and plugins, blocking of malicious IPs and domains, isolation of a compromised machine, and one policy set by your security team.
Differential
Pre-signature malware (MEW) at registry publication
Malware across packages, containers, pipelines, commits.
CI/CD pipeline security: GitHub Actions, build infra, secrets.
Typosquatting & obfuscated-payload detection
Native SLSA + in-toto build attestations + CBOM
Detects only publicly known malicious packages
Dependency check inside the CI pipeline only
Runs in the pipeline — doesn’t secure it.
No typosquatting / behavioral analysis
SBOM generation; no native attestations.
Yes, if you need more than code quality. Xygeni covers code quality and adds SAST, SCA, secrets, CI/CD security, DAST, pre-signature malware detection and ASPM in one platform, with AI triage and fixes delivered as pull requests.
Yes. Xygeni enforces quality gates on pull requests and can fail a build. Gates are baseline aware, so teams are blocked on the new issues a pull request introduces, not on historical debt.
It fixes them. AI Remediation proposes the change and opens a pull request, and findings are ranked by remediation complexity so teams see what they can clear first.
No. The scanner runs inside your infrastructure with read-only access, and only results are uploaded. Xygeni also runs fully on-premise and air-gapped.
Yes. It runs in the same scanner and reports into the same console, with the same AI triage, remediation and prioritization as security findings.
Bring the questions your SonarQube evaluation left open. We will walk through them on your stack.
