AI code review

Catch risky codebefore it ships

Security issues, bugs, and messy patterns - explained in plain language with fixes you can apply in minutes. Run the same review on pull requests with a GitHub Action or paste code in the web dashboard - structured recommendations on your diffs.

  • Security & correctness - find mistakes that reviews and linters often miss.
  • Actionable output - grouped findings, not a wall of generic advice.
How it works

No credit card to try · Free code review · Privacy policy

Sample review · TypeScript

Quality score

Based on language best practices

78/ 100

Issues found

2 issues
  • Warning·Lowroutes/users.ts:56

    Handler is long and deeply nested - early returns would make the flow easier to follow.

  • Warning·Mediumvalidation.ts:17

    Same email checks in two places - extract a shared validateEmail() helper.

Δ validation.ts +14 −6·routes/users.ts +2 −8

What you get

Reviews that feel like a senior dev - at machine speed

Structured, fast, and private. Paste a snippet or connect a repo and get feedback you can act on today.

Structured feedback

Grouped by theme and severity - triage fast.

Seconds, not hours

Paste code or hook GitHub - get a full pass quickly.

Your workspace

Reviews stay with your account. Details in Privacy.

Language coverage

25+ languages, one pipeline

Paste a snippet, upload a file, or wire GitHub - we infer the stack from what you send. No manual language tags.

Full catalog

Config, data, and markup formats included - reviews follow what is in the buffer.

Where teams ship most often

JavaScript

Top tier

JavaScript

TypeScript

Top tier

TypeScript

Python

Top tier

Python

Java
JavaPopular
C#
C#Popular
Go
GoPopular
Rust
RustPopular

Indexed language hubs

Each page explains what our pipeline looks for in that ecosystem - security seams, packaging edges, and how much surrounding context helps the model stay grounded.

JavaScriptTypeScriptPythonGoRust

Beyond syntax

Findings tie to changes you can ship

We are not showing fake before/after blocks here - those belong in a real review on your code. This is the kind of output you get next to your files: explanations, and proposed code changes when the review can supply them.

Readability & idioms

Naming, control flow, and structure - when a clearer pattern exists, you get the explanation plus a concrete edit where it fits.

Typical in

JS, TS, Python, Go, Ruby, PHP, and most application code.

Correctness & edge cases

Empty inputs, off-by-one risks, and error paths - feedback points at the line that needs a guard or a safer default, not a lecture in the abstract.

Typical in

Any language; depth grows with file and repo context.

Security & risky APIs

Injection, trust boundaries, and dependency signals show up when the review has enough context - not from a one-line snippet on a marketing page.

Strongest with

Full files, linked modules, or a connected repo.

In the product, findings come with narrative context and, when applicable, suggested code - plus severity, categories, and line references for your stack.

Evidence in production

Teams pairing AI review with humans

Composite stories from anonymous engineering leaders - specifics intentionally generalized. Metrics belong in your own retros, not our marketing banners.

How AI and human reviewers split the work →

Director of engineering · fintech (150 engineers)

Reduced noisy nits before humans opened the PR

The team wired CodeCritic ahead of human reviewers so every pull request surfaced blocking security items and duplication early. Humans still approve merges, but calmer threads made weekly review budgets measurable again.

“We wanted automation to shorten the blunt part of review, not to publish auto-LGTM rubber stamps. Structured findings gave us that split.”

Platform lead · SaaS infrastructure

Brought outsourced contractors onto the same quality bar

Short-term contractors were shipping valid features yet missing internal logging standards. Automated review caught missing structured fields before staff reviewers repeated the lecture in comments.

“Contractors reacted faster when feedback referenced exact lines plus suggested patches - reviewers spent time on architecture instead.”

Staff engineer · data platform team

AI pass before database migrations

Schema PRs ran through CodeCritic to flag unsafe defaults, transactional gaps, and language-specific footguns prior to pairing sessions with DBAs.

“The model does not bless migrations - it gives the team a briefing doc so specialists focus on blast radius conversations.”

Interested in contributing a publishable testimonial later? Email support@code-critic.com with “case study” in the subject line.

Workflow

Input once, review once, ship with confidence

Three stages your team already thinks in - spelled out so nobody mistakes us for another chat box. Open the app for scores, file scope, and the full run.

Get code into CodeCritic

Meet the workflow you already use.

  • Paste in the browser, upload a file, or connect a GitHub repo for reviews that need project context.
  • Languages are inferred in the product - you are not stuck tagging files by hand.

Read one structured report

Skip the wall of generic chat.

  • Issues roll up by theme and severity so you can triage what blocks a release versus what can wait.
  • Security, bugs, and maintainability show up in a single pass - explained in plain language.

Close the loop in your repo

From finding to fix without guesswork.

  • Feedback ties to lines and suggested changes where it helps - not vague advice.
  • Apply fixes, re-run if you want, then merge when the diff matches your bar.

Generic AI chat

  • "Consider improving your code quality overall."
  • Long paragraphs. No file context. Hard to assign or track.
  • You still guess what to fix first.

CodeCritic review

Each item pairs a clear explanation with a proposed code change when one makes sense - not suggestions-only chatter.

  • Security

    Why this call is risky, line references in the app, and often a concrete hardening or validation snippet.

  • Correctness

    Edge cases called out with reasoning - plus a suggested guard, early return, or fix you can apply as code.

  • Maintainability

    Clearer idioms and structure - explanation first, then a proposed refactor or diff-style edit when it helps.

Stylized examples - real reviews list severities, messages, and suggested code where the model can propose it.

Ready when you are

Same flow from the dashboard - paste, upload, or repo. Free tier to start; limits apply by plan.

No card required to sign up

How it works

From the code you have to a merge you trust

Not another three-step infographic - this is the shape of the product: boundary in, structured review, clear exit.

  • Wire in what you already have

    A snippet for a fast gut check, a file when the whole module matters, or a GitHub repo when context lives across folders. Detection runs in the app - you are not configuring parsers here.

  • One pass that reads like a review

    Findings roll up by severity and theme - not a single blob of text. Each item explains why it matters, points at lines, and often includes a proposed code change when one is appropriate.

  • A handoff you can act on

    You leave with a prioritized view of what to fix before merge - and what is already solid. No guessing order, no copying advice out of a chat window.

Compare plansFull guide

Plans

Simple pricing

Start free. Upgrade when you need more reviews or team features.

Questions

Answerswithout the fluff

Grouped by topic. Open one at a time to stay focused - or jump to the full guide.

Using CodeCritic

Workflow, languages, and what you get back.

Paste your code in the web editor or use our GitHub Action on pull requests. Our AI analyzes it for bugs, security issues, style, and best practices. Results appear in 5–30 seconds. We support 25+ languages with auto-detection.
25+ languages including JavaScript, TypeScript, Python, Java, C#, Go, Rust, PHP, Ruby, Swift, Kotlin, C++, and more. The language is auto-detected from your code.
Yes. Every account gets an API key and GitHub Action integration. The integrations hub summarizes OAuth, webhooks, CI templates, and optional custom LLM HTTPS routing. For step-by-step wiring see the Help guide.
Bugs, security issues, performance problems, style violations, and best-practice suggestions. Each finding includes an explanation and actionable recommendations.
Usually 5–15 seconds. Larger codebases may take up to 30 seconds. You get instant feedback with detailed explanations.

Data & trust

What happens to your code and how to read suggestions.

No. Your code is processed in real-time and discarded after analysis. We never store it permanently or use it to train models. Your privacy and intellectual property are protected.
Suggestions are recommendations, not rules. Evaluate them in the context of your project. CodeCritic explains the reasoning so you can decide what to apply.
Read the dedicated AI code review limitations FAQ for procurement-style questions on accuracy, compliance expectations, and escalation paths.
Humans still own nuanced product judgment. Use automation to widen hygiene coverage quickly, then keep humans on risk decisions. Compare roles on AI versus human review.

Plans & workspace

Limits, teams, billing, and your review history.

It depends on your plan. All plans - free and paid - have monthly review limits. You can also buy pay-per-use credits. Check the Pricing section for current plans and limits.
Yes. Teams can use the web interface, API, and GitHub Action for consistent code reviews. Company plans include team management and shared usage.
A free plan is available to try the service. For other inquiries, please contact our support team.
Yes. All reviews are saved in your dashboard. You can access them anytime and export as needed.

Still stuck?

Read the step-by-step guide, replay the workflow on the page, or email us - we respond on business days.

User guideSee workflowEmail support

Ready to review your next PR?

Join in seconds. Run a free review, then scale with plans when your team needs more.

See workflow