Open Source Greptile Alternatives
A curated collection of the 2 best open source alternatives to Greptile.
The best open source alternative to Greptile is Kodus. If that doesn't suit you, we've compiled a ranked list of other open source Greptile alternatives to help you find a suitable replacement. Other interesting open source alternative to Greptile is Pullfrog.
Greptile alternatives are mainly AI Assisted Coding. Browse these if you want a narrower list of alternatives or looking for a specific functionality of Greptile.
AI code review that runs inside your pull requests, follows rules you write in plain language and uses your own model keys.
Kodus puts an AI reviewer called Kody directly into the pull request, where it reviews with context, flags risks by severity and suggests concrete fixes rather than summarizing the diff. The README walks through it catching an IDOR risk where an organization id passed as an array could bypass tenant protection.
It is model agnostic. Claude, GPT-5, Gemini, Llama, GLM, Kimi or any OpenAI-compatible endpoint connects with your own provider credentials, so billing stays on your account with no markup on model costs. It works natively with GitHub, GitLab, Bitbucket and Azure Repos, and runs from a CLI locally or inside a pipeline.
Several pieces sit around the review itself.
- Kody Rules: review instructions written in plain language and scoped to an organization, repository, path or review type.
- Kody Issues: unimplemented suggestions from closed pull requests are tracked by status, severity and category, then resolved when a later PR fixes them.
- Cockpit: review effectiveness, rule health, repository health and delivery metrics in one dashboard.
- Token usage: consumption is tracked across reviews so model spend stays predictable as adoption grows.
- Privacy: source code is not used to train models, and data is encrypted in transit and at rest.
The project is AGPLv3 licensed, with documentation in six languages. Self-hosted instances send one anonymous daily heartbeat of aggregated counters, with no code, names or identifiers, and an environment variable turns it off. Self-hosted runners suit teams who cannot send source code outward, while a managed cloud covers anyone who would rather not deploy anything at all.
Runs coding agents inside your own GitHub Actions to review pull requests, fix broken CI and triage issues on your keys.
Pullfrog listens for GitHub events, pull requests opened, issues created, reviews submitted, CI failures, and triggers agent runs from a workflow file in your repository. Because the runs happen in your Actions, you keep the infrastructure, the keys and the bill, which is the part that usually decides whether a review bot is worth adopting.
It is not an agent itself. It wraps Claude Code, Codex and OpenCode, picking whichever matches your configuration, so every run uses the vendor's real agent and reads the repo-level setup you already keep for it: CLAUDE.md or AGENTS.md, skills, custom commands and MCP servers.
Each automation toggles from the dashboard and takes its own per-trigger instructions.
- Review new PRs: incoming pull requests get an automatic review whose verdict can gate merges as a required status check.
- Address review comments: leave feedback as you would for a colleague and it works through the thread.
- Autofix: failing CI on its own pull requests and merge conflicts are fixed without hand-resolution.
- Triage issues: apply labels, answer common questions, link related work or draft an implementation plan.
- Ad hoc requests: tag it in any issue, pull request or comment and it pulls in the surrounding context.
- Contained execution: GitHub operations use a short-lived installation token that is revoked when the run ends, shell commands run in an isolated subprocess, and keys are masked in logs.
Setup takes about two minutes through one npx command or the browser console. It is free for personal accounts and open source repos.
