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Qodo AI

From Qodo

Quality-First AI Code Review Platform for Accurate Issue Detection and Enterprise Trust
Tool Release Date

1 Jan 2022

Tool Users
1 Million+
0.0

Pricing Model

Starting Price

$0/Month

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About This AI

Qodo AI (formerly CodiumAI) is an advanced AI code review platform that helps engineering teams standardize code quality, detect critical issues early, and accelerate development with high-signal, context-aware reviews.

It integrates into IDEs, pull requests, CLI, and Git workflows to provide agentic issue finding, real-time local reviews, compliance checks, automated resolutions, and enforcement of organization-specific standards.

Powered by a state-of-the-art context engine (used by NVIDIA) and multi-agent architecture, it analyzes full repository signals including codebase history and prior PR decisions for precise, explainable feedback with reduced noise.

Key capabilities include shift-left reviews (catch bugs/missing tests while coding), PR validation against security policies and ticket traceability, and 15+ agentic workflows to scale reviews matching AI development speed.

Founded in 2022 by Itamar Friedman (ex-Alibaba AI Lab) and Dedy Kredo, Qodo has raised $50M, serves over 1 million developers, and is adopted by Fortune 100 companies including NVIDIA, Monday.com, and Box.

It outperforms competitors in precision/recall for critical issues (highest F1-score in benchmarks) and addresses the trust gap where 96 percent of developers hesitate to ship AI-generated code without review.

With SOC2 compliance, data privacy focus (only necessary code analyzed, SSL encrypted), and both SaaS/on-prem options, Qodo is built for enterprise-scale code integrity in high-velocity AI-assisted environments.

Key Features

  1. Agentic issue finding: Context-aware detection of critical bugs, logic gaps, security risks, and standards violations
  2. Local IDE reviews: Real-time guidance with precise suggestions and instant resolutions while coding
  3. Compliance and PR validation: Enforces security policies, ticket traceability, and org-specific rules automatically
  4. Automated issue resolution: Fixes problems before commit with verified code changes
  5. Shift-left quality checks: Catches issues early in development to reduce downstream rework
  6. Multi-agent architecture: Leverages full repo context including history and prior decisions for accuracy
  7. Deep context engine: Enterprise-scale search and retrieval for high-signal, low-noise feedback
  8. 15 plus agentic workflows: Scales reviews to match AI code generation velocity
  9. Explainable feedback: Provides clear reasoning for suggestions to build developer trust
  10. Privacy and compliance: SOC2 certified, SSL encrypted, analyzes only necessary code

Price Plans

  1. Free ($0): For open-source projects; up to 250 credits per calendar month (1 credit per LLM request, higher for premium models like Claude Opus/Grok 4)
  2. Teams (Contact for pricing): 2500 credits per calendar month, includes advanced features for teams (contact sales for exact cost)
  3. Enterprise (Contact us): All-in-one intelligent review platform with PR/IDE/CLI tools, context engine, dashboard, SSO, priority support, SaaS/on-prem, proprietary models; custom pricing

Pros

  1. Highest benchmark accuracy: Leads in precision/recall for critical issues and low noise
  2. Enterprise adoption: Used by NVIDIA, Monday.com, Box, and Fortune 100 companies
  3. Trust-building focus: Addresses 96 percent developer hesitation on AI code with reliable reviews
  4. Deep context awareness: Full repo history and signals for superior understanding
  5. Speed and scale: Matches fast AI development with automated, consistent quality gates
  6. Privacy-first design: Strong security, compliance, and minimal data exposure
  7. Flexible deployment: SaaS or on-prem options for enterprise needs

Cons

  1. Pricing not fully public: Free tier for open-source, but Teams/Enterprise require contact
  2. Credit-based limits: Usage tied to credits (e.g., 250/month free, 2500 Teams); resets monthly
  3. Setup for enterprise: On-prem or advanced features need custom configuration
  4. Focus on review: Primarily quality/review layer; less emphasis on pure generation
  5. Recent rebrand: Transition from CodiumAI may cause minor confusion in discovery
  6. Dependency on AI models: Performance tied to underlying LLM quality and context handling

Use Cases

  1. AI-assisted code review: Automatically catch bugs/security issues in PRs or IDE
  2. Shift-left quality enforcement: Detect problems while coding to reduce rework
  3. Enterprise compliance: Validate against security policies and traceability rules
  4. High-velocity development: Scale reviews to match rapid AI code generation
  5. Team standardization: Enforce consistent coding/security standards across repos
  6. Trust in AI code: Verify and improve AI-generated code before shipping
  7. Multi-repo analysis: Provide deep context across large codebases

Target Audience

  1. Engineering teams: In complex, multi-repo environments needing quality gates
  2. Enterprise developers: Fortune 100 companies focused on security/compliance
  3. AI-heavy teams: Using generative AI but requiring reliable review layer
  4. Open-source contributors: Leveraging free tier for personal/projects
  5. DevOps and platform engineers: Automating standards enforcement
  6. Security-conscious organizations: Prioritizing policy validation in SDLC

How To Use

  1. Sign up: Create account on qodo.ai for free tier or contact for Teams/Enterprise
  2. Install extensions: Add IDE plugin (VS Code/JetBrains), GitHub App, or CLI
  3. Configure: Set up org-specific rules, policies, and preferred AI models
  4. Code and review: Get real-time suggestions in IDE or automated PR comments
  5. Resolve issues: Accept AI fixes or get guided changes for quick resolution
  6. Monitor compliance: View dashboard for enforcement and quality metrics
  7. Scale with workflows: Use 15 plus agentic flows for advanced automation

How we rated Qodo AI

  • Performance: 4.8/5
  • Accuracy: 4.9/5
  • Features: 4.7/5
  • Cost-Efficiency: 4.5/5
  • Ease of Use: 4.6/5
  • Customization: 4.8/5
  • Data Privacy: 4.9/5
  • Support: 4.5/5
  • Integration: 4.7/5
  • Overall Score: 4.7/5

Qodo AI integration with other tools

  1. IDE Plugins: VS Code, JetBrains for real-time local reviews
  2. GitHub App: Automated PR reviews, compliance checks, and issue resolution
  3. CLI Tools: Command-line interface for workflow integration
  4. Enterprise Systems: SSO, on-prem deployment, dashboard for governance
  5. AI Models: Compatible with various LLMs for flexible review intelligence

Best prompts optimised for Qodo AI

  1. Not applicable - Qodo AI is a code review and quality platform that analyzes code automatically in IDE/PR/CLI; no manual prompting required for core functionality.
Qodo AI stands out as a quality-first AI code review platform with exceptional accuracy in detecting critical issues and enforcing standards across the SDLC. Its deep context engine and agentic workflows make it ideal for enterprise teams shipping AI-generated code confidently. Free for open-source and contact-based pricing for teams/enterprise offer strong value for complex codebases.

FAQs

  • What is Qodo AI?

    Qodo AI is an AI code review platform that provides context-aware issue detection, automated resolutions, compliance checks, and quality enforcement in IDEs, PRs, CLI, and Git workflows.

  • When was Qodo AI founded?

    Qodo (formerly CodiumAI) was founded in 2022 by Itamar Friedman and Dedy Kredo.

  • How many developers use Qodo AI?

    Over 1 million developers have installed Qodo, with adoption by Fortune 100 companies including NVIDIA, Monday.com, and Box.

  • Is Qodo AI free to use?

    Yes, a free tier is available for open-source projects (250 credits/month); Teams and Enterprise plans require contacting sales for custom pricing.

  • What makes Qodo AI different from other code review tools?

    It leads in precision/recall for critical issues, uses deep repo context/history, reduces noise, and builds trust in AI-generated code with explainable feedback.

  • Does Qodo AI support enterprise deployment?

    Yes, it offers SaaS or on-prem options, SSO, priority support, and proprietary models for enterprise needs.

  • What integrations does Qodo AI support?

    Native integrations with IDEs (VS Code, JetBrains), GitHub, CLI tools, and enterprise systems for workflows.

  • Is Qodo AI secure and compliant?

    Yes, SOC2 certified, SSL encrypted, analyzes only necessary code, and focuses on privacy/security for enterprise use.

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