What Is ScanDrix And How Does It Work?

ScanDrix is an autonomous AI-powered code review and AST security scanning platform built for modern engineering teams. It integrates into your Git providers (GitHub, GitLab, Bitbucket, Azure Repos) to automatically review pull requests, detect vulnerabilities, suggest code fixes, and enforce custom Drixy rules.

How Does ScanDrix Differ From Traditional Linters Like SonarQube?

Traditional linters analyze files in isolation using rigid regex or pattern rules, resulting in high false-positive rates and zero understanding of code intent. ScanDrix performs deep Abstract Syntax Tree (AST) analysis combined with multi-model AI reasoning, understanding whole-codebase context, taint flows, and architectural boundaries.

What Are Drixy Rules And How Do I Configure Them?

Drixy rules are customizable code review and security policies. You can define rules globally across your organization, per repository, or choose from a library of community best practices. You can also run 'Dry Run' previews to test rule modifications against real historical PRs before enforcing them.

Which Git Providers And CI/CD Tools Does ScanDrix Support?

ScanDrix supports GitHub, GitLab, Bitbucket, Azure Repos, and Forgejo out of the box. It also provides a CLI and team API keys for local developer workflows, pre-commit hooks, and custom CI/CD runners.

Does ScanDrix Train On Our Private Source Code?

No. ScanDrix never uses customer source code to train AI models. All code diffs are processed in ephemeral, isolated environments with strict zero-data-retention guarantees. For enterprise deployments, ScanDrix supports Bring Your Own Key (BYOK) and self-hosted on-premise installations.

How Fast Are ScanDrix Code Reviews On New Pull Requests?

ScanDrix is built for sub-minute reviews: an async worker architecture picks up webhook events without blocking CI pipelines. That is a design goal, not a measured guarantee — live service state is on the status page.

Can ScanDrix Suggest Inline Code Fixes?

Yes. When ScanDrix detects bugs, security vulnerabilities, or rule violations, it generates precise inline diff suggestions directly in the pull request review comments that developers can apply with a single click.

Can We Deploy ScanDrix On-Premise Or In Our Own VPC?

Yes. Enterprise customers can deploy ScanDrix in their own AWS, GCP, or Azure VPC, or in fully air-gapped on-premise environments with support for internal LLM endpoints (vLLM, Ollama) and enterprise SSO.

Same corpus · same bar · independently audited

Compare architectures.

We compare against the three tools teams actually ask us about — architecture to architecture, not scoreboard to scoreboard.

Comparisons: 3 architectural
Scores: None invented
Basis: Public product facts
Updated: See each page

ScanDrix vs

CodeRabbit

Both are AI reviewers. The difference is what the model is shown: a prompt over a diff, or a compiled AST it can query.

Context sourceCross-file reasoningSelf-hostingPricing model

Full comparison

ScanDrix vs

GitHub Copilot

Copilot's strength is autocomplete, where it is excellent. PR review is a different job with a different accuracy bar.

Primary productDetection on large PRsSecurity focusWhere it fits

Full comparison

ScanDrix vs

SonarQube

A decade of pattern-matching quality gates versus an AST engine that reasons about data flow. Both are legitimate — for different jobs.

Analysis modelFalse positivesTurnaround timeMigration path

Full comparison

How we compare

Three axes only.

Vendor comparisons usually cherry-pick one flattering metric. These three decide whether a review tool survives contact with a real engineering team.

Detection accuracy

Share of seeded vulnerabilities flagged at the correct file and line — not flagged somewhere in the repo.

Review speed

Median wall-clock time from pull request event to posted review, measured under concurrent load.

False positives

Share of flags a senior engineer judged incorrect, established by manual audit of every finding.

Want the testing methodology behind our own claims? See how we evaluate ourselves.

Judge it on your own code.

Architecture is comparable from public facts; accuracy is not — that you can only judge on your repositories. So run it and decide.

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