Qodo is the AI code review platform that helps teams catch critical issues early, reduce review noise, and maintain consistent code quality across fast-moving, AI-driven development.
Qodo is the enterprise AI code review platform that ensures quality scales with AI-driven development. Our agents run across the IDE and Git with shared cross-repo context and organization-specific rules to deliver precise, high-signal reviews. The result is cleaner code, faster review cycles, and higher-quality software across teams, repositories, and AI-generated development.
Highlights
Multi-agent code review in your Git: Qodo runs specialized agents across every PR to write descriptions, flag real issues with remediations, and enforce your team's governance and security standards at scale, all with full codebase context. (GitHub, GitLab, Bitbucket, Azure DevOps)
Cross-repo codebase context: Review code against your full, cross-repo codebase to catch breaking changes, dependency conflicts, architecture-level issues, and other hidden risks.Agentic review automation: Build configurable, specialized review agents with shared context to enforce code quality rules, use tools to execute specific review tasks
A centralized rules system to define and enforce organizational standards across the repository - security policies, coding and style standards, architectural conventions, and compliance requirements, applied consistently to all pull requests so quality holds at scale.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
You choose between two contract options based on developer count. The Trial Teams option covers 5 developers, while the Teams option covers 50 developers. Both bundle the same two products: qodo Gen and qodo Merge. Pricing scales by team size, so you pick the option that matches how many developers need access. These are packaged seat-based contracts, not usage-based billing.
Top-of-mind questions for buyers
What products are included in each contract, and what do they do?
Both contracts bundle qodo Gen and qodo Merge. qodo Merge runs AI pull request review inside Git, finding issues and enforcing standards. qodo Gen supports code generation and review across the development workflow. The same two products come with either the 5-developer or 50-developer option.
What happens if my developer count grows beyond the contract I chose?
Each contract covers a fixed developer count: 5 developers for Trial Teams or 50 developers for Teams. To support more developers than your contract allows, you move to the option that matches your team size. Pick the developer count that fits your team.
Does this platform limit how many repositories or code reviews I can run?
No. You can install on as many repositories as you want and run reviews across them. The contract meters developer access, not repository count or review volume. Both options support review across pull requests, local pre-commit checks, and cross-repo change detection.
Request a private offer to receive a custom quote.
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AWS Marketplace subscribers are entitled to our Standard Support: support@qodo.ai
Enterprise customers receive priority support and a dedicated CSM.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Specialized agents run across pull requests to write descriptions, flag issues with remediations, and enforce governance and security standards across GitHub, GitLab, Bitbucket, and Azure DevOps.
Cross-Repository Codebase Context
Review code against full cross-repository codebase to detect breaking changes, dependency conflicts, and architecture-level issues using shared organizational context.
IDE-Integrated Local Code Review
Review workflows execute within the IDE to analyze local changes, identify bugs, and flag security or compliance issues before pull request submission.
Configurable Specialized Review Agents
Build and configure specialized review agents with shared context to enforce organization-specific code quality rules and execute specific review tasks.
AI-Driven Development Support
Platform designed to handle code review at scale for AI-generated development with high-signal reviews and reduced review noise.
AI-Powered Code Generation and Review
Automated merge request generation based on user stories and AI-driven merge request reviews integrated into development workflows
Unified DevSecOps Platform
Comprehensive platform covering the entire software development lifecycle with integrated security and compliance controls from commit to production
Multi-Step Workflow Automation
AI agents capable of executing complex, multi-step tasks including test generation, code upgrades, and deployment workflow automation
Enterprise Security and Compliance
Built-in enterprise-grade security controls with unified platform for automating secure code deployment and reducing risk across the development pipeline
Integrated Development Environment Integration
Direct embedding of AI capabilities into GitLab daily workflows with unified data store for streamlined operations across AWS and GitLab
Multi-Language Code Support
Supports analysis and navigation across multiple programming languages within enterprise codebases
Distributed Codebase Navigation
Enables instant access to code context across multiple repositories, branches, and code hosts at enterprise scale
Code Change Compliance Verification
Ensures accuracy, compliance, and consistency of human and AI-driven code changes across the organization
Enterprise-Scale Performance
Maintains performance and functionality across large, complex, and fragmented codebases including monoliths and microservices
AI Agent Integration
Provides code understanding and context capabilities for AI agents to operate effectively on real-world enterprise code
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