Qodo vs Sourcegraph Cody

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Qodo

Qodo is an AI code review platform designed to bring automated context aware review into IDE and pull requests across Git workflows, using a credit based usage model and offering a Free tier with monthly credit limits plus team and enterprise plans for governance and support.

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Sourcegraph Cody

Sourcegraph Cody is an AI coding assistant built for complex codebases that integrates with major code hosts and editors, supports enterprise controls like data isolation and audit logs, and emphasizes code understanding at scale so teams can reuse prompts and standardize quality.

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At a glance

QodoSourcegraph Cody
PriceFree / $30 per user per month / Custom pricingCustom pricing
DifficultyBeginnerBeginner
TypeWeb AppWeb App
StatusActiveActive

Qodo — Key features

  • Credit based limits: Uses monthly credits with a stated Free tier limit that helps teams plan evaluation volume
  • Git workflow coverage: Positioned to work across IDE pull requests and CI CD steps in common Git based workflows
  • Context aware feedback: Aims to surface issues earlier by considering codebase context beyond single file diffs
  • Support tiers: Describes community standard and priority support with different response expectations
  • Data retention policy: States paid subscriber data is stored briefly for troubleshooting and not used to train models
  • Opt out option: States free tier users can opt out of data use for model improvement via account settings

Sourcegraph Cody — Key features

  • Code host integration: Works with common code hosts so Cody can reference real repository context instead of pasted snippets
  • Major editor support: Designed to work with major editors so developers keep their existing workflow and tooling
  • Enterprise security controls: Highlights data isolation zero retention no model training audit logs and controlled access for compliance
  • Model choice: Mentions access to latest-gen LLMs that do not retain data or train on your code per the product page
  • Prompt reuse governance: Encourages sharing and reusing prompts to automate tasks and promote best practices across teams
  • Scale for large codebases: Designed to handle large repositories and large files so context stays usable at enterprise scale

Qodo — Best for

  • Pull request review: Add automated comments to PRs to catch issues early and reduce review latency for busy teams
  • Style enforcement: Use consistent review guidance to reinforce coding standards and reduce manual nitpicks in reviews
  • Regression prevention: Flag risky changes and missing tests so reviewers focus on correctness and coverage
  • Onboarding support: Help new contributors understand repository conventions through guided review feedback
  • CI review gate: Use AI review signals alongside tests to prioritize what needs deeper human attention

Sourcegraph Cody — Best for

  • Large repo onboarding: Help engineers understand unfamiliar repositories faster by asking questions grounded in codebase context
  • Refactor planning: Draft refactor approaches and check impacts across multiple modules with prompts guided by repository structure
  • Code review support: Summarize changes and suggest review checklists that align to internal standards and common pitfalls
  • Documentation drafting: Produce initial docs and READMEs from code context then enforce human review for accuracy and tone
  • Migration assistance: Generate migration steps and helper code while tracking patterns across repositories and services