The agentic engineering lanscape is largely fragmented. There are tools that write your code, others that review it, and others that deploy it. Each has its own context, its own model, its own subscription. The promise of AI-accelerated development gets eaten alive by the friction of stitching it all together.
Standalone AI code review tools like CodeRabbit bolt onto your workflow rather than living inside it. They lock you into a single vendor's model choices. They leave you context-switching between disconnected products.
Code Reviews in Kilo is built on a different premise. It's part of the Kilo agentic engineering platform, where it lives in the same ecosystem as the agents writing, debugging, and deploying your code.
The Problem With Locked-In AI Stacks
Most AI code review tools lock you into their AI stack. They pick the model, they decide when to upgrade, and you get whatever they've configured. That works fine until it doesn't. Maybe it's not the best model for your stack, maybe it's slow, or maybe a better option emerges and you're stuck waiting for your vendor to adopt it.
The agentic engineering landscape is moving fast. Kilo Code Reviews was built for that reality---because lock-in costs more when everything's still changing.
With access to 500+ models, you pick the model that reviews your code. Need fast, lightweight feedback on routine PRs? Use a faster model, like MiniMax M2.1. Working on security-critical infrastructure that needs deeper reasoning? Switch to something with deeper reasoning - like Claude Opus 4.5.
The model that's best for reviewing new React components might not be the best for reviewing ancient Rust systems, and now you don't have to pretend otherwise.
Pricing That Doesn't Scale Against You
CodeRabbit charges $24 per seat per month, just for code reviews.
Kilo works on per-token pricing at the cost set by model providers. You pay for the reviews you run, which means you don't leave money on the table, and you don't hit invisible rate limits or downgrades when you surpass an arbitrary usage limit.
Right now, Kilo for Teams is $15/seat/month, and gets your team centralized access to the entire Kilo platform, plus:
Usage analytics & reporting
AI adoption scores
Shared agent modes
Centralized billing
Shared BYOK
Team management
Data privacy controls
Priority support.
Kilo was built for teams and individuals that value transparent pricing, scalable systems, and frictionless development workflows --- and the same applies to Code Reviews.
Part of Your Workflow, Not Another Tool
CodeRabbit is a standalone code review product. It does one thing, and you add it to your existing pile of dev tools.
Kilo's Code Reviews is part of the Kilo platform, the same environment where you're already writing code, debugging, and deploying. Your reviews happen alongside:
Agentic Engineering with specialized modes for implementation, architecture, debugging, and orchestration in the IDE or CLI
Cloud Agents for accessing Kilo without using your local machine
App Builder for prototyping with a live preview
Kilo Sessions that sync across VS Code, JetBrains, CLI, and web
Kilo Deploy for one-click shipping when the review passes
Managed Indexing for context-aware reviews that understand your codebase
No platform switching. No lost context. No added friction.
Customization That Fits Your Style
Kilo gives you control over how reviews work:
Review Styles
Strict: Flags everything. For security-critical code and production services.
Balanced: The default. Catches what matters without drowning you in noise.
Lenient: Light touch for prototypes, WIP branches, and exploratory work.
Focus Areas
Pick what the reviewer prioritizes: security vulnerabilities, performance issues, bug detection, code style, test coverage, or documentation gaps.
Custom Instructions
Add your own rules. Your team's conventions, your domain-specific patterns, your edge cases. The reviewer applies them automatically.
Getting Started
Code Reviews is available now in the Kilo Dashboard at https://app.kilo.ai/code-reviews. To enable:
Connect your GitHub account via the Integrations tab
Enable AI Code Review in the Code Reviews tab
Choose your model, review style, and focus areas
Select which repositories should receive automatic reviews
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