Octopus

Octopus is an AI code-review tool that indexes repositories and reviews pull requests with help from a configured language model. It is best suited to teams that want shared review guidance and a choice of Git provider, AI provider, or deployment model. Its strongest case is repository-aware feedback with room to control the setup; teams using the hosted service should weigh its data-retention terms.

Overview

When a pull request opens, Octopus uses vector search to retrieve relevant indexed code, then sends that context and the diff to a configured language model. Findings are severity-rated and posted as inline comments. Repository context can help teams apply their own conventions, but the model remains responsible for analysis.

On GitHub, reviews run when a pull request opens or changes; Octopus also posts check runs and can create issues from findings. Source-cited codebase chat and a CLI for reviews, context queries, and repository-state checks give developers ways to work with repository knowledge outside the review itself.

Key features

• Shared review standards: Knowledge-base documents can guide reviews, while team rules, repositories, and reviewer settings are shared across an organization. That suits teams seeking consistent criteria; it is less compelling for someone who only needs an individual checker.
• Choice of AI provider: Supported options include Anthropic Claude, OpenAI, Google, xAI Grok, Alibaba Qwen, Cohere, and OpenRouter. Teams can use a provider they already work with, though the Cloud Usage-Based plan charges more than the provider's list price.
• Broad Git-provider support: Octopus supports GitHub, GitLab, Bitbucket, and Forgejo. GitLab supports self-hosted instances, and private Forgejo can connect through a local connector. The GitHub workflow has the most specifically described automation: reviews, comments, check runs, and issue creation.
• Deployment control: Self-hosting uses Docker Compose with PostgreSQL and Qdrant. Teams can optionally run review models and embeddings locally through Ollama, which gives them an alternative to hosted processing but requires them to operate the deployment.
• Security and retention: HTTP traffic uses TLS 1.2 or higher, and OAuth tokens for listed third-party integrations are encrypted row by row using AES-256. Hosted Octopus stores review and indexing data: findings remain for the pull request's lifetime and 90 days after closure, while indexed embeddings remain as long as the repository is connected. That retention may not suit teams with stricter deletion requirements.

Pricing

Octopus has a free self-hosted option and a free cloud tier, plus a usage-based cloud plan. There is no free trial; the cloud free tier instead includes sign-up credits. No seat or review quota is stated for these plans.

Live team telemetry requires a paid organization, defined as any credit purchase or bring-your-own-key setup. The free cloud tier includes community support; users can also report issues and contribute through GitHub.

Platforms

Octopus supports API, Linux, macOS, Windows, web, and self-hosted use. Its listed code hosts are GitHub, GitLab, and Bitbucket, with Forgejo also supported.

Who it's for

Octopus is a strong fit for engineering teams that want automated, context-aware pull-request feedback and shared review rules, especially when provider choice or self-hosting matters. It is also practical for teams that want source-cited codebase questions and CLI access alongside reviews. Look elsewhere if you need live team telemetry without paying or supplying your own key, or if hosted retention does not meet your requirements.

Pros and cons

• Pros: Indexed repository context informs reviews; shared rules and documents can align feedback across a team; GitHub, GitLab, Bitbucket, and Forgejo support provides deployment flexibility; self-hosting and optional local models offer control over the AI setup.
• Cons: Hosted review findings persist 90 days after pull-request closure and embeddings persist while a repository remains connected; the usage-based cloud plan bills at twice the provider's list price; live team telemetry is reserved for paid organizations.

Alternatives

Consider CodeRabbit if you want a freemium tool with a free trial and free reviews forever for public repositories. Choose Cubic if a defined free allowance of 20 PR reviews a month for public repositories fits your needs, or if its Team plan at $30 a month, billed yearly, suits your budget.

DeepSource may suit open-source teams looking for unlimited public repositories and unlimited team members, with 1,000 pull request reviews per month in its Open Source plan. LiveReview is another freemium alternative to compare.

ThinkReview is worth considering if its Lite plan's 15 review credits per day, support for pull requests up to 40,000 lines, and up to three custom review agents per pull request match your workflow. Ironwood AI may be a better fit if you prefer a paid product with a 30-day Evaluation plan for two developers and one active installation.

Choose AI Code Reviewer if you want a free, Linux or self-hosted option where you pay only your model provider's usage. Codacy is an alternative if you want an IDE plugin supporting 38 programming languages and integrations with VSCode, JetBrains, and Cursor.

Browse more options in AI Code Review Tools or Code review software.

Verdict

Choose Octopus if your team wants code-aware pull-request reviews, shared review standards, and flexibility over AI provider and deployment. Its repository context and self-hosting options are the clearest reasons to choose it. Look elsewhere if hosted data retention is unsuitable or the cloud plan's token markup does not fit your expected usage.