CodeKang
AI-powered PR reviews with contextual analysis and automated fixes.
At a glance
- Editor score9.6 / 10
- PricingFree plan · paid from $19/user/mo · 14-day trial
- Best forSmall teams wanting affordable contextual review
- Free planYes
- Paid from$19/user/mo
- Automated analysisYes
- Facts checked19 Sep 2026
Where it wins
- Repository history and dependency context improve PR review relevance.
- AST-based analysis covers security, performance, and logic issues.
- Automated fix pull requests and review analytics support follow-through.
Where it doesn't
- Code-host support is limited to GitHub, GitLab, and Bitbucket.
- The Free plan covers only 5 private repositories and basic summaries.
- Advanced capabilities require paid plans or the Enterprise tier.
Our verdict on CodeKang
CodeKang is an AI code-review platform for engineering teams that want pull-request analysis with more context than a change-only scan. It uses repository history and dependency context to review code, adds inline comments and risk scores, and analyzes logic, security, performance, and architectural issues. The product is aimed at small teams that want affordable contextual review, while its team-oriented features also support larger engineering groups.
The freemium pricing structure gives teams a clear progression. Free includes 5 private repositories, basic AI summaries, and public repository access. Starter costs $19 per seat per month and adds unlimited private repositories, full PR reviews, Jira and Linear sync, and a 14-day free trial. Team costs $79 per 20 seats per month and adds unlimited repositories, autonomous fix pull requests, unit test generation, and analytics reports. Enterprise includes SSO/SAML, a self-hosting option, a dedicated customer success manager, and a 99.9% uptime SLA.
CodeKang’s main depth is its combination of contextual review, AST-based detection, and fix verification. It can identify issues such as SQL injection, secrets, null dereferences, N+1 queries, and race conditions, then use sandboxed test execution to verify fixes. Review analytics cover cycle time, PR health, and velocity metrics, while integrations extend across GitHub, GitLab, Bitbucket, Jira, Linear, Slack, Discord, Notion, Vercel, Sentry, Datadog, PostHog, and Segment. Teams should choose CodeKang when automated review and remediation fit their workflow; organizations needing support beyond those three code hosts should consider an alternative.
CodeKang pricing
All 4 CodeKang plans and prices →
CodeKang fact sheet
| Free plan | Yes |
|---|---|
| Paid from | $19/user/mo |
| Supported code hosts | GitHub, GitLab, Bitbucket |
| Automated analysis | Yes |
| AI code review | Yes |
| Custom review rules | Yes |
| Security analysis | Yes |
| Review analytics | Yes |
| Self-hosted deployment | Yes |
| Free trial | 14 days |
| Deployment | Cloud |
| Platforms | Web |
| Integrations | 13 integrations: GitHub, GitLab, Bitbucket, Jira, Linear, Slack … |
| Pricing | Free plan · paid from $19/user/mo · 14-day trial (source) |
| Website | codekang.com |
| Facts checked | 19 Sep 2026 |
CodeKang integrations
CodeKang lists 13 integrations on its own site.
- GitHub
- GitLab
- Bitbucket
- Jira
- Linear
- Slack
- Discord
- Notion
- Vercel
- Sentry
- Datadog
- PostHog
- Segment
Alternatives to CodeKang
- BitoA broad code-review platform for teams that want analysis across hosts, tools, and workflows.10.0
- SourceryBroad AI review and security coverage with a free plan and paid team features.10.0
- PR-AgentA flexible, self-hosted PR review agent with broad integrations and configurable AI workflows.—
See all CodeKang alternatives →
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Reviewed by iTechGuides Editors · Editorial team · Updated Sep 2026
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