Ironwood AI reviews code using AI providers selected by the team and engineering context such as coding standards, architecture documents, requirements and technical guidance. It presents findings with evidence for engineers to inspect, and teams can review multiple repositories in one batch, including cross-repository analysis when service boundaries matter. Listed source-control integrations are GitHub, Azure DevOps and Bitbucket; delivery integrations include Jira, Azure Boards and Confluence. Supported AI providers include OpenAI, Anthropic Claude, Google Gemini and Ollama. Ironwood runs on infrastructure the customer controls, with local Admin, Reviewer and Viewer roles. The customer manages credentials. With a hosted AI provider, prompts and selected code or context are sent to that provider; Ollama can keep the AI request inside the customer's infrastructure. Professional includes PDF reports, role-based access control, platform health and diagnostics. Evaluation offers 30 days of Professional features for two developers and one active installation. Professional costs $15.00 USD per month; Team costs $200.00 USD per month for up to 20 developers. AI-provider usage is billed separately.
Who it is for
Ironwood is aimed at engineering teams that want AI-assisted code review while retaining control over their code, providers and review decisions. It may suit teams that need batch review across repositories and want to supply their own engineering guidance.
What is good
- Reviews can include coding standards and architecture documents.
- Batch review supports cross-repository analysis.
- Runs on customer-controlled infrastructure.
- Ollama can keep AI requests inside customer infrastructure.
- Professional and Team have unlimited repositories and reviews.
What to know first
- Evaluation is limited to two developers and one active installation.
- AI-provider usage is billed separately.
- Enterprise pricing is by agreement and not listed.
Verdict
Ironwood pairs evidence-bearing code review with customer-managed infrastructure and configurable review context. Teams should account for separate AI-provider charges and decide whether hosted-provider data flow fits their requirements.
Ironwood AI plans and pricing
All plansCompared on AI code review tools
- Free plan
- No
- Custom review rules
- Yes
- Deployment model
- self_hosted
- Review trigger
- manual
- Code hosts
- GitHub, Azure DevOps, Bitbucket
