How CodeAnt AI Boosted Developer Productivity for Good Glamm Group
How CodeAnt AI Boosted Developer Productivity for Good Glamm Group
How CodeAnt AI Boosted Developer Productivity for Good Glamm Group
October 07, 2024
October 07, 2024
October 07, 2024
About
About
About
The Good Glamm Group, a global leader in beauty and personal care, has rapidly expanded with over $430 million in funding and a $1.2 billion valuation. Their engineering team faces the challenge of keeping their digital platforms secure and scalable while swiftly delivering new features to meet growing customer demands.
The Good Glamm Group, a global leader in beauty and personal care, has rapidly expanded with over $430 million in funding and a $1.2 billion valuation. Their engineering team faces the challenge of keeping their digital platforms secure and scalable while swiftly delivering new features to meet growing customer demands.
Challenge
Challenge
Challenge
As the company scaled, so did the complexity of its codebase. Good Glamm Group’s development teams were spending excessive time on code reviews and security assessments, delaying product releases. Manual processes slowed down their speed of delivery, and false positives from security tools further drained productivity, forcing developers to focus on irrelevant issues instead of true risks.
To maintain its competitive edge, Good Glamm Group needed a solution that could significantly reduce review times, improve code security, and increase the overall quality of the codebase without adding unnecessary overhead.
As the company scaled, so did the complexity of its codebase. Good Glamm Group’s development teams were spending excessive time on code reviews and security assessments, delaying product releases. Manual processes slowed down their speed of delivery, and false positives from security tools further drained productivity, forcing developers to focus on irrelevant issues instead of true risks.
To maintain its competitive edge, Good Glamm Group needed a solution that could significantly reduce review times, improve code security, and increase the overall quality of the codebase without adding unnecessary overhead.
Solution
Solution
Solution
Good Glamm Group turned to CodeAnt AI, the world’s first AI + deterministic rule-based code reviewer, to overcome these challenges. By leveraging CodeAnt AI’s advanced features, the team experienced significant improvements:
50% Faster Code Reviews – CodeAnt AI’s code review automation reduced the manual effort required by developers, cutting review time in half. With over 30,000 built-in rules across 30+ languages, the solution offered comprehensive coverage, ensuring that all aspects of the code were thoroughly vetted for issues and potential risks.
Improved Security – CodeAnt AI’s application security (SAST) features minimized false positives, ensuring that developers focused only on real security threats. This reduction in noise helped streamline the security review process.
Customizable Rules for Better Code Quality – Beyond the built-in rules, Good Glamm Group took advantage of CodeAnt AI’s capability to manage and write custom rules in plain English, tailoring code reviews to their specific project requirements. This helped maintain high standards of code quality, regardless of the programming language or framework used.
Good Glamm Group turned to CodeAnt AI, the world’s first AI + deterministic rule-based code reviewer, to overcome these challenges. By leveraging CodeAnt AI’s advanced features, the team experienced significant improvements:
50% Faster Code Reviews – CodeAnt AI’s code review automation reduced the manual effort required by developers, cutting review time in half. With over 30,000 built-in rules across 30+ languages, the solution offered comprehensive coverage, ensuring that all aspects of the code were thoroughly vetted for issues and potential risks.
Improved Security – CodeAnt AI’s application security (SAST) features minimized false positives, ensuring that developers focused only on real security threats. This reduction in noise helped streamline the security review process.
Customizable Rules for Better Code Quality – Beyond the built-in rules, Good Glamm Group took advantage of CodeAnt AI’s capability to manage and write custom rules in plain English, tailoring code reviews to their specific project requirements. This helped maintain high standards of code quality, regardless of the programming language or framework used.
Champion
Champion
Champion
Alpesh Jain, VP of Engineering, along with Akshay Sanklecha, Senior Manager, championed the adoption of CodeAnt AI.
Alpesh Jain, VP of Engineering, along with Akshay Sanklecha, Senior Manager, championed the adoption of CodeAnt AI.
Results
Results
Results
Good Glamm Group achieved remarkable results:
50% faster code reviews, allowing the engineering team to release features more quickly without compromising on quality or security.
Enhanced code security, with fewer false positives and better focus on actual vulnerabilities, improving developer productivity.
Better code quality across the board, aided by the AI-driven reviews and customizable rules that ensured consistency and reliability in every release.
Good Glamm Group achieved remarkable results:
50% faster code reviews, allowing the engineering team to release features more quickly without compromising on quality or security.
Enhanced code security, with fewer false positives and better focus on actual vulnerabilities, improving developer productivity.
Better code quality across the board, aided by the AI-driven reviews and customizable rules that ensured consistency and reliability in every release.
Conclusion
Conclusion
Conclusion
With CodeAnt AI, Good Glamm Group not only boosted productivity but also improved the overall security and quality of their codebase. By automating time-consuming tasks and reducing noise from false positives, developers could focus on innovation and delivering value to customers.
With CodeAnt AI, Good Glamm Group not only boosted productivity but also improved the overall security and quality of their codebase. By automating time-consuming tasks and reducing noise from false positives, developers could focus on innovation and delivering value to customers.
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Made with Love at San Francisco
355 Bryant St. San Francisco, CA 94107, USA
Copyright © 2024 CodeAnt AI.
All rights reserved.
Product
Comparison
Resources
Made with Love at San Francisco
355 Bryant St. San Francisco, CA 94107, USA
Copyright © 2024 CodeAnt AI.
All rights reserved.
Product
Comparison
Resources