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.

Self-Hosted Deployment

Run ScanDrix inside your own VPC or on-prem — Docker Compose, Kubernetes, and air-gapped setups.

Enterprise deployments run entirely within your network: AWS, GCP, or Azure VPC, or a fully air-gapped on-premise environment.

What you get

Code never leaves your network (bring internal LLM endpoints: vLLM or Ollama).
Same product surface: dashboard, rules, Dry Runs, CLI, Cockpit metrics.
Enterprise SSO and your own secret management.

Requirements

Item	Minimum
Compute	4 vCPU / 8 GB RAM (API + worker + web)
Database	PostgreSQL 15+, MongoDB 6+
Queue	RabbitMQ 3.12+ with delayed-message exchange plugin
Object storage	S3-compatible bucket (or local volume for small installs)
LLM access	Internal endpoints (vLLM/Ollama) or BYOK egress allow-list

Docker Compose (standard install)

bash

# 1. Unpack the release bundle
tar -xzf scandrix-selfhosted-<version>.tar.gz && cd scandrix

# 2. Configure
cp .env.example .env
$EDITOR .env   # set SCANDRIX_SECRET, DATABASE_URL, LLM_BASE_URL...

# 3. Start the stack
docker compose up -d

# 4. Create the first admin
docker compose exec api scandrix bootstrap-admin --email admin@example.com

Open the dashboard on port 8080 (or your reverse proxy's hostname — see Reverse Proxy & TLS).

.env holds real secrets — database URLs, signing keys, provider credentials. Keep it out of version control and load it from your platform's secret manager in production.

Kubernetes

Helm chart with the same components (api, worker, relay, web, postgres, mongodb, rabbitmq):

bash

helm repo add scandrix https://charts.scandrix.dev
helm install scandrix scandrix/scandrix \
  --namespace scandrix --create-namespace \
  --set image.tag=<version> \
  -f values.production.yaml

values.production.yaml should reference your existing managed database/queue endpoints rather than the chart-bundled ones.

Air-gapped notes

Mirror container images and the CLI binary to your internal registry.
Point LLM_BASE_URL at an internal inference server (vLLM/Ollama) — no egress required.
License file is offline-validated; no phone-home telemetry (telemetry can be disabled entirely).

Upgrades

bash

docker compose pull && docker compose up -d

Schema migrations run automatically at startup and are backward-compatible for one minor version — upgrade one minor at a time. Keep a database backup before each upgrade; rollback = restore backup + previous image tag.

Health checks

Endpoint	Purpose
`GET /healthz`	Liveness — process is up
`GET /readyz`	Readiness — DB + queue reachable
`/metrics`	Prometheus scrape (workers expose queue depth)

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