AI Code Reviewer 2.0

Code review that actually understands your system

CloudAEye doesn't stop at the diff. It evaluates your change across dependencies, configurations, and runtime services to deliver architect-level reviews.

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4x Faster Merge Times

3x More Bugs Caught

0 Learning Curve

Beyond the PR

CloudAEye take into context all the repos, their dependencies when reviewing a PR

Full codebase context and Control Flow

Deep Cross-Repo Intelligence

CloudAEye isn't limited to the lines you changed. It indexes your entire codebase, spanning multiple repositories, to detect how a minor tweak can break a distant service that wasn't even touched.

Cross repo traking: Follows changes from your PR into downstream services.
Module tracking: Analyze how files, functions, classes, modules, and dependencies relate to each other.

analytics-pkg

design-sys

PR #1094

web-frontend

📦

payment-sdk

v2.0.1

⚙️

core-engine

📝

logger

billing-svc

BREAKING API

📝 payment_controller.ts

1 import { Stripe }
                            from
                            'stripe';2 3 const stripe =
                            new
                            Stripe(process.env.API_KEY);
                              AI
                            

                              cloudaeye-devprod: According to
                              Stripe v12 Docs, the `apiVersion` parameter is now mandatory.
                            
4 5 async function
                            processPayment(amount)
                            {6   try {7     const
                            intent =
                            await
                            stripe.paymentIntents.create({8       amount:
                            amount,9       currency:
                            'usd',10     });11   } catch (e)
                            {12     console.error(e);13   }14 }

Stripe API Reference

Reading Documentation...

✓ Docs Loaded

Checking constructor signatures for breaking changes in v12.0...

Techstack Aware

Fluent in your stack

CloudAEye understands your frameworks, cloud and CNCF technologies, to provide reviews similar to a senior architect.

Best practices: Provides best practices for the technologies used in the repo.
Library descripency: Flags deprecations, incompatibility and risky upgrades.

Continuous Learning

Customize Review to suit your style

CloudAEye doesn't just run static checks. It adapts to your team's review style, custom rules, and feedback so future reviews feel more and more according to your style.

Learning

Point CloudAEye at PRs that have human reviews, and it will learn from those comments and decisions to mirror your team's review style.

Rules

Capture your standards as custom rules, including naming conventions, security patterns, logging requirements, and anything unique to your codebase, and apply them across every new PR automatically.

Feedback

Tell us when a reported issue isn't useful and we'll turn it into a rule, so the same kind of noise doesn't show up again in future reviews.

Code Security

Replace fragmented tools with one cohesive check. We bundle industry standard analysis engines directly into the review process.

🛡️

SAST

Static Application Security Testing finds vulnerabilities like SQL injection and XSS.

📦

SCA Analysis

Software Composition Analysis scans your dependencies for known CVEs, licensing issues, and risky packages.

🔑

Secret Scanning

Prevents hardcoded credentials, API keys, and tokens from ever reaching your main branch.

Agentic workflows

AI agents, LLM, and MCP review

CloudAEye reviews code that uses AI agents to scan for any security vulnerabilities. Code is reviewed against OWASP top 10 vulnerability detection and the Agentic Security Initiative (ASI) by default

AI Agent: Understands patterns for building, orchestrating, and securing AI agents.
LLM checks: Flags prompt issues, unsafe outputs.
MCP Report: Reviews Model Context Protocol integrations, tools, and wiring for correctness and safety.

Code Quality

Comphrehensive review of code quality, style and bugs analysis

Linter Support

Honor your linters and style guides

CloudAEye runs alongside your lint rules, surfacing violations, and keeping your style consistent across repos.

Custom rule sets: ESLint, Prettier, Pylint, and multiple other linters supported.

Bug Detection

PR Quality

CloudAEye reviews code that uses AI agents to detect code quality issues.

PR Description: Auto add PR description based on code changes.
Commit Description: Auto add description for all commits in a PR.
Bug Report: Find issues before they hit production.

Auto Review

Trigger reviews automatically

Start code reviews automatically so every change matches your standards.

Filters: Include or exclude PRs by labels, branches, author, or keywords.

Developer productivity

Help engineers get familiar with the existing codebase faster, so they can ship changes with confidence.

Ask

Detailed answers about any part of your codebase

Get precise, context-aware answers to your questions so that you can get familiar with the code flow in minutes.

Whole codebase search: Ask across repos, services.
Faster onboarding Unblock new developer without waiting on tribal knowledge.

Implement

Fix review issues

Apply recommended fix for a code review issue with confidence.

Suggested fixes: Concrete code changes that will help you quickly fix an issue

Add Docs

Documentation to your codebase

Let users add and keep their own documentation in sync so docs stay aligned with latest code.

Docs in context: Answers and suggestions cite your docs, not guesses.

Test

Generate unit tests

Create targeted unit tests for new changes and edge cases, aligned with your frameworks and patterns.

Framework-aware: Generates tests for your stack (e.g., Jest, PyTest, JUnit).
Edge coverage: Exercises boundary conditions, null/undefined, and error paths.
Style aligned: Matches your project conventions and directory layout.

Explain

Analyze and resolve issues

Feed any issue and CloudAEye pinpoints root causes and gives concrete steps to fix them.

Maps to code: Identifies likely files, functions, and commits involved.
Actionable fixes: Suggests clear remediation steps or code changes.

Data Privacy

Your code and data stay confidential

We do not store your actual source code.
CloudAEye has established Zero Day Retention (ZDR) policy agreements with both OpenAI and Anthropic. These contracts ensure that your data remains strictly confidential and is never used for model training purposes. All data transmitted to the models is secured using TLS encryption.
We offer a deployment option where all your data is hosted within your Virtual Private Cloud (VPC), providing complete control and enhanced security.

For details on retention, access controls, and compliance, see our Privacy Policy.