# How Apica uses Bito

**83%**: “achieving 83% faster pull request cycles”

As published on [bito.ai](https://bito.ai/case-studies/apica/), September 2025. Captured by usedby on 2026-10-04.

- Company: [Apica](https://www.usedby.ai/companies/apica.md)
- Tool: [Bito](https://www.usedby.ai/tools/bito.md)
- Industry: [DevTools & Infrastructure](https://www.usedby.ai/companies/industry/devtools-infrastructure.md)
- Teams: Engineering

## What the story says

Apica's engineering team uses Bito's AI Code Review Agent to flag issues in pull requests before human review, across GitHub and Bitbucket. This reduces the review load on a small group of reviewers and helps catch bugs earlier.

Summary written by usedby from the source page, in English. The figures are those of Bito and Apica, not ours.

> Before Bito, reviewing a PR could take an hour or more. Now, submitters fix most issues before a human reviewer sees the code. This means reviewers spend only 10 to 20 minutes on most PRs, even for large ones.

- **530+**: “530+ PRs reviewed”
- **271,780+**: “271,780+ lines of code analyzed”
- **330+**: “330+ issues flagged by Bito”
- **54.1%**: “54.1% acceptance rate of Bito’s suggestions”

> Bito gives targeted, context-aware feedback that reduces the load on reviewers and improves overall quality. It’s a valuable part of our daily development workflow.
>
> Kumar Vishnu, Director of Engineering

## What usedby checked

We compared the story with its live page on 2026-10-04.

- Checked: the figure 83% is printed word for word on the page, near the name of Apica.
- Checked: the passage quoted above is copied word for word from the page, near the name of Apica.
- Checked: the publication date is read from the page’s own metadata, never guessed.
- Checked: Apica uses Bito. Confirmed line. Latest check across sources: 2026-10-04.
- Not checked: the result itself. We quote it; we did not measure it.

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Source: https://www.usedby.ai/case-studies/apica-bito · How we check: https://www.usedby.ai/methodology