--- title: Automating Code Reviews with AI: How Halodoc Scaled... description: Halodoc built an AI-powered code review system embedded in their Jenkins Global Library CI/CD pipeline, reducing Merge Request feedback time from 30–45 minutes... canonical: https://daily.dev/posts/automating-code-reviews-with-ai-how-halodoc-scaled-quality-across-the-full-stack-ozrzjr8ty twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Automating Code Reviews with AI: How Halodoc Scaled Quality Across the Full Stack | daily.dev og:description: Halodoc built an AI-powered code review system embedded in their Jenkins Global Library CI/CD pipeline, reducing Merge Request feedback time from 30–45 minutes... og:url: https://daily.dev/posts/automating-code-reviews-with-ai-how-halodoc-scaled-quality-across-the-full-stack-ozrzjr8ty og:image: https://api.daily.dev/og/posts/oZRzjr8tY.png og:image:alt: Automating Code Reviews with AI: How Halodoc Scaled Quality Across the Full Stack og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Automating Code Reviews with AI: How Halodoc Scaled Quality Across the Full Stack **[Halodoc](https://daily.dev/sources/halodoc)** · 14 min read · 1 upvotes · 0 comments ## Summary Halodoc built an AI-powered code review system embedded in their Jenkins Global Library CI/CD pipeline, reducing Merge Request feedback time from 30–45 minutes to 1–2 minutes. The system uses two LLMs — Gemini CLI for fast diff-based reviews and Claude Sonnet via AWS Bedrock for deeper contextual analysis — with stack-specific prompts covering Java, Angular, Swift, Kotlin, SRE, and Data Engineering repositories. A Comment Lifecycle Manager prevents duplicate discussions and auto-resolves fixed findings. Over six months, the platform processed 58,811 review invocations (~9,800/month) at roughly $1,600–$1,700/month in inference costs, with 85% of findings accepted by developers. Key lessons: prompt engineering and guardrails matter more than model selection, and lifecycle management is essential for developer trust. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Automating MR Reviews: How Halodoc Reduced SQL Review Time Using AI](https://daily.dev/posts/automating-mr-reviews-how-halodoc-reduced-sql-review-time-using-ai-yrsz88ctd) · Halodoc · 1 upvotes · 0 comments - [Orchestrating AI Code Review at scale](https://daily.dev/posts/orchestrating-ai-code-review-at-scale-re4wh2np4) · Cloudflare · 0 upvotes · 0 comments --- Tags: [#cicd](https://daily.dev/tags/cicd), [#ai-coding](https://daily.dev/tags/ai-coding), [#prompt-engineering](https://daily.dev/tags/prompt-engineering), [#gitlab](https://daily.dev/tags/gitlab), [#jenkins](https://daily.dev/tags/jenkins) [View this post on daily.dev](https://daily.dev/posts/automating-code-reviews-with-ai-how-halodoc-scaled-quality-across-the-full-stack-ozrzjr8ty) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Automating Code Reviews with AI: How Halodoc Scaled Quality Across the Full Stack","url":"https://daily.dev/posts/automating-code-reviews-with-ai-how-halodoc-scaled-quality-across-the-full-stack-ozrzjr8ty","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/automating-code-reviews-with-ai-how-halodoc-scaled-quality-across-the-full-stack-ozrzjr8ty"},"datePublished":"2026-07-10T06:47:38.651Z","dateModified":"2026-07-10T08:21:45.331Z","description":"Halodoc built an AI-powered code review system embedded in their Jenkins Global Library CI/CD pipeline, reducing Merge Request feedback time from 30–45 minutes...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/884b54ec4ba52f2854d1a3e59291eace?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/884b54ec4ba52f2854d1a3e59291eace?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Halodoc","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Halodoc","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/b3d554a1a7b44df48789c7ca6e50c4c2","url":"https://daily.dev/sources/halodoc"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/automating-code-reviews-with-ai-how-halodoc-scaled-quality-across-the-full-stack-ozrzjr8ty","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":1},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"cicd,ai-coding,prompt-engineering,gitlab,jenkins","timeRequired":"PT14M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Halodoc","item":"https://daily.dev/sources/halodoc"},{"@type":"ListItem","position":3,"name":"Automating Code Reviews with AI: How Halodoc Scaled Quality Across the Full Stack"}]} ```