Bito's AI Code Review Agent | Merge PRs 90% faster

BTO's AI code review integrates directly into GitHub, GitLab, and Bitbucket, both cloud and enterprise. We never store your code or train our AI on your code.

In four minutes, I'm going to show you four major things. One, we summarize your PR and provide detailed line level feedback with one click except suggestions. Two, BTO's agent fully

suggestions. Two, BTO's agent fully understands your repo and brings that knowledge to the code review. Three,

detailed ways to learn about your coding style and patterns means BTO review fits into your team built for enterprises.

And four, we provide a host of detailed analytics that let you learn about what kinds of issues are popping up the most, which repos are having trouble, etc. Let's show it to you. The AI code review agent fits within your normal workflows.

You can set it up in 5 minutes. As soon

as a PR is submitted, it automatically runs. Let's take a look at the output.

runs. Let's take a look at the output.

I've got a PR here for my team. Let's

look at what the bidto agent says.

First, our code reagent builds multiple indices such as abstract syntax trees and symbol indices on the flying as well as uses agentic reasoning to deeply understand your large codebase.

We summarize your PR right at the top here. This doesn't require any comments

here. This doesn't require any comments or documentation from your team. This is

100% produced by Bidto's agent.

Then we give you a change list which explains the key changes in your PR and which files comprise that change. This

is really helpful for reviewers. Now

let's walk through the detailed feedback. Bids flag that you have an

feedback. Bids flag that you have an unsafe list type casting which is going to cause a runtime exception. If you

look at the fetch network data method, it's returning a link list. But the data processor constructor underneath it being cast to an array list which is going to cause a runtime exception. Now,

how do bid figure this out? It uses a deep agentic reasoning and its ability to read and understand through your codebase to explore what's happening.

First, it looks at the application. Java

file and sees that the fetch network data method is instantiating the data processor constructor.

When it looks at the data processor constructor, it sees that it's being cast to an array list. As we talked about before, at this level, we're casting it as a link list, which is going to cause this runtime exception.

We then provide you a code suggestion to use it and change it to an array list, and you can oneclick apply this or apply it in a new commit as a batch. Bidto

deeply learns your team's practices and guidelines. We have the ability for you

guidelines. We have the ability for you to customize by adding guidelines. You

can use one of our pre-formatted templates with many different guidelines by language or by security, or you can create your own guideline.

Bid's agent also learns from your team's feedback to tune out suggestions that they don't want.

Lastly, Bid provides detailed analytics to help you learn where your team is struggling and to understand the impact code reviews having. You can see here

that 2,000 code reviews were done across 38 submitters, about a 50% acceptance rate across a number of different categories of feedback.

We also provide detailed analytics at the language and repo level to show you the types of issues that are happening and to help you coach your team.

The agent is available to run in Bidos's cloud that you can configure by logging into BTO.AI or as a Docker image you can run in your own private cloud. Vid's AI

code review is cutting open to merge times by 90% and reducing buds by 40%.

Step into the next era of best-in-class code reviews.