How Good Glamm Group cut code review time by 50%
Faster code review
Built-in rules scanned
False positives
Problem
Manual reviews and noisy security scans overwhelmed developers, slowed releases, and drained productivity as Good Glamm’s codebase scaled.
Solution
CodeAnt AI automated reviews, cut review time in half, minimized false positives, and enforced consistent quality across the growing engineering org.
Founded
2017
Valuation
$1.2 Billion
Industry
Beauty & Personal Care
Code Hosting
Bitbucket
About Good Glamm Group
Founded in 2017 and now valued at $1.2B, The Good Glamm Group is a global beauty and personal care leader backed by $430M+ in funding. With fast growth across digital platforms, their engineering team faced the dual challenge of delivering new features at speed while maintaining the security and scalability of their applications.
CodeAnt AI cuts code review time by 50%.
The PR review feature helps identify potential issues and efficiently trace them back. Application Security capabilities report minimal false positives, meaning developers can focus on real issues.
— Alpesh Jain, VP Engineering at Good Glamm Group
How CodeAnt AI Transformed Good Glamm Group
Good Glamm replaced slow manual reviews and noisy security tools with one AI-powered platform for code reviews, security, and quality.
The Challenge Before AI
As Good Glamm scaled its digital footprint:
Manual reviews slowed releases — every PR demanded too much time from engineers.
False positives drained productivity — noisy scans distracted from real vulnerabilities.
Inconsistent quality checks — standards varied across repos and teams.
Security gaps emerged — manual processes missed critical edge cases.
Pressure to move faster — without adding overhead or sacrificing reliability.
The AI Breakthrough
With CodeAnt AI embedded in Bitbucket, Good Glamm Group automated reviews and security checks without disrupting developer workflows:
50% faster reviews — automation halved review time, freeing engineers to ship features faster.
Smarter security — SAST with minimal false positives kept the focus on real threats.
Custom rules — plain-English rule creation tailored reviews to internal standards.
Comprehensive coverage — 30,000+ built-in checks across 30+ languages and frameworks.
Measurable Outcomes
50% faster code reviews → features shipped quicker without compromising quality.
Stronger security → fewer false positives, sharper focus on real vulnerabilities.
Higher code quality → custom rules enforced consistency across all repos.
One Platform for Complete Code Health
With CodeAnt AI, Good Glamm Group replaced manual reviews and noisy tools with a single AI-driven platform that enforces quality, strengthens security, and saves developer time.
