Code Airlock vs Codegen

Detailed side-by-side comparison to help you choose the right tool

Code Airlock

🔴Developer

developer-tools

A thin CLI wrapper around Docker Sandboxes that runs Claude Code, Codex, or OpenCode in a disposable microVM against a clone of your repo, then brings the work back as ordinary git commits for review.

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Starting Price

Custom

Codegen

🔴Developer

Developer Tools

AI developer agent platform for enterprise teams with sandboxed execution, governance controls, and deep workspace integration.

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Starting Price

Custom

Feature Comparison

Scroll horizontally to compare details.

FeatureCode AirlockCodegen
Categorydeveloper-toolsDeveloper Tools
Pricing Plans6 tiers6 tiers
Starting Price
Key Features

      Code Airlock - Pros & Cons

      Pros

      • Real security boundary at the microVM level — not just agent-side prompts
      • Host repo stays read-only; every change comes back as a reviewable git commit
      • Multi-agent: swap between Claude Code, Codex, OpenCode with one flag
      • Sandbox never needs GitHub creds — PRs push from the host
      • MIT licensed with npm/Homebrew/curl installs and preflight `doctor` diagnostics

      Cons

      • Requires Docker Sandboxes and KVM/virtualization on the host
      • No MCP integration — wraps agents but doesn't extend their tool surface
      • Extra latency vs. running the agent directly on the host
      • Small project (thin wrapper) — you're also depending on the underlying sbx CLI
      • Adds cognitive load: another layer between you and the agent

      Codegen - Pros & Cons

      Pros

      • Enterprise-grade governance and compliance (SOC 2) that competing tools lack
      • Parallel agents dramatically speed up large codebase refactoring
      • Full workspace context including project management tools, not just code
      • On-premises deployment available for regulated industries
      • PR Review Agent catches security and architectural issues at org level
      • Reproducible runs with full audit trails for every agent action

      Cons

      • Pricing not publicly disclosed — enterprise sales process required
      • Overkill for small teams or individual developers
      • Newer platform with less community adoption than Cursor or Copilot
      • Learning curve for configuring governance policies and agent workflows
      • Limited public documentation on performance benchmarks vs competitors

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