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CodeRabbit is an AI-first pull request reviewer founded in 2023 that delivers context-aware feedback, line-by-line code suggestions, and real-time chat. It integrates with GitHub and GitLab, offers continuous AI-driven code security, and is trusted by 17,000+ engineering teams.
Read-only public captures of CodeRabbit’s homepage and verified pricing page. Screenshots are dated, never live embeds, and open full-screen.
Short answers to the questions buyers and builders commonly ask about CodeRabbit. Each answer cites the shared ledger below, where every source is listed once.
AI-first pull request reviewer with context-aware feedback, line-by-line code suggestions, · Post-Merge Actions that use pull request context to handle changelogs, documentation, tick · Catches 95%+ of bugs in code reviews · Auto-generates PR summaries
AI-first pull request reviewer with context-aware feedback, line-by-line code suggestions, and real-time chat.
Engineering teams shipping software created by people and agents · General audiences and users 13 and older · Engineering teams, including junior engineers on distributed teams
the team building an independent control layer for software created by people and agents so engineering teams can scale judgment.
Continuous code security using reachability, exploitability, and blast radius analysis on · AI code review that catches 95%+ bugs for engineering teams · Engineering teams use CodeRabbit to reduce review time, catch critical issues, and improve · First-pass AI code reviewer before human review
Continuous code security, run by AI agents. Reachability, exploitability, and blast radius analysis on every PR and across the whole codebase.
CodeRabbit Security | $40/mo/user | Usage-based add-on · CodeRabbit Agent for Slack | $0.50 per agent minute | Pay only for what you use
CodeRabbit Security $40/mo/user Usage-based add-on
Jira and Linear integrations · MCP connections: 5 on Pro, 15 on Pro Plus, 20 on Enterprise · Worked with NVIDIA and Baseten to post-train NVIDIA Nemotron 3.5 Lightning for routing tas · VS Code and Cursor IDE extensions for inline AI feedback
Jira and Linear integrations
Reviews run in isolated, secure environments
Reviews run in isolated, secure environments
This profile connects the jobs CodeRabbit is described as handling with its delivery model, access options and the subjects used to match it to related products in this directory.
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Agentic Change Management | CodeRabbit
AI-first pull request reviewer with context-aware feedback, line-by-line code suggestions, · Founded in 2023 · Integrates with GitHub and GitLab
AI-first pull request reviewer with context-aware feedback, line-by-line code suggestions, and real-time chat
Continuous code security using reachability, exploitability, and blast radius analysis on every PR and across the whole codebase
GitHub and GitLab
CodeRabbit Security | $40/mo/user | Usage-based add-on
CodeRabbit Agent for Slack | $0.50 per agent minute | Pay only for what you use
Jira and Linear integrations
MCP connections: 5 on Pro, 15 on Pro Plus, 20 on Enterprise
Reviews run in isolated, secure environments
Source code is not retained after a review completes (except optional encrypted review caching that expires automatically and is never used for training)
A concise view of the jobs, capabilities and integrations described in the recorded product sources.
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Showing the newest updates and meaningful milestones. Open an entry for its summary and source.
CodeRabbit Security was introduced as an application-security product with a Hunt, Verify, and Fix workflow that traces suspected vulnerabilities across the codebase and proposes reviewable fixes inside the pull-request workflow.
View source [18]CodeRabbit Security launched, tracing application-specific vulnerabilities across the repository, evaluating reachability against code evidence, and proposing reviewable fixes inside the pull request workflow.
View source [18]CodeRabbit announced a $143M Series C at a $1.5B valuation and introduced its Agentic Change Management platform, covering review, triage, prioritization, and security for AI-generated code changes.
View source [21]CodeRabbit worked with NVIDIA and Baseten to post-train Nemotron 3.5 Lightning (SFT then RLVR) for PR routing, raising exact route agreement from 75.8% (GPT baseline) to 80.7% and cutting estimated inference cost by ~50%.
View source [23]Essay arguing that better AI models sharpen what agents write but do not resolve the human-judgment bottleneck on what deserves to merge into shared systems.
View source [20]Facts, answers, structured details, milestones and primary resource links cite this shared ledger. Each external page appears once; release tags from the same GitHub project are grouped under one release history.
Free reviews forever for public repositories installed via GitHub or GitLab
2023
AI-first pull request reviewer with context-aware feedback, line-by-line code suggestions, and real-time chat
AI code review that catches 95%+ bugs for engineering teams
Engineering teams shipping software created by people and agents
Build an independent control layer for software created by people and agents so engineering teams can scale judgment
2023
CodeRabbit
$143 million Series C raise at a $1.5 billion valuation
Agentic Change Management, the control layer for software changes created by humans and agents
Traces suspected vulnerabilities across the codebase, evaluates reachability and exploitation conditions, and proposes reviewable fixes in pull requests
Post-Merge Actions that use pull request context to handle changelogs, documentation, tickets, and other post-merge work
Worked with NVIDIA and Baseten to post-train NVIDIA Nemotron 3.5 Lightning for routing tasks
https://discord.gg/coderabbit
CodeRabbit, Inc.
2023
AI-first pull request reviewer with context-aware feedback, line-by-line code suggestions, and real-time chat
Catches 95%+ of bugs in code reviews
VS Code and Cursor IDE extensions for inline AI feedback
Java, Go, Node, Python, Kotlin, PHP, Scala, and Android native
Coordinates multiple models for layered reasoning and contextual analysis
Auto-generates PR summaries
Engineering teams use CodeRabbit to reduce review time, catch critical issues, and improve code quality across real-world projects
General audiences and users 13 and older
Most installed AI App on 6M repositories; trusted by 17K customers
AI-first pull request reviewer with context-aware feedback
Line-by-line code suggestions
Real-time chat for code review
Essay arguing that as coding agents expand change volume, the bottleneck shifts from producing code to understanding it, and review needs a traceable path from intent to system behavior to code.
View source [14]