AI for developers

14 workflows. Tickets to tested pull requests, first-pass reviews, changelogs, postmortems and dependency upgrades. Work your team keeps putting off.

$149/month per workspace · Unlimited people · AI usage billed by your provider

69%
of developers lose eight or more hours a week to inefficiencies. Atlassian, State of Developer Experience 2024

All engineering workflows.

14 workflows

See how engineering teams use Maito

Where AI helps an engineering team.

Maito works in your repositories. It turns a ticket into a tested pull request, reviews a teammate's pull request, checks a change for security problems and upgrades a dependency on a branch. Around the code, it files a bug from a Slack thread, drafts the incident postmortem from the channel and logs, investigates an error spike, and writes the changelog on a schedule.

Engineers keep every decision that ships. An engineer reviews and merges each pull request, the author decides what to fix from a review, and an engineer decides on a rollback when an error spike shows up. A security lead signs off where needed. Maito does not merge code, and it does not change production.

Start with a small ticket you would hand to a new hire. Connect your repository and issue tracker, then mention @Maito in the ticket's Slack thread and ask for a pull request. Read the diff as you would any other. Once you trust the output, set up the weekly engineering digest or the stale pull request nudge as a Loop.

Questions.

Put your AI teammate to work.

Set it up in minutes. Start with one workflow, and let it earn the next one.