What challenges did Palo Alto Networks face before AI implementation?

Palo Alto Networks needed to boost software developer productivity and code quality while ensuring strict security compliance across its complex codebases. Traditional onboarding and code review processes were time-consuming and resource-intensive, limiting developer efficiency. There was a need for scalable AI-driven tools integrated into the development lifecycle to accelerate software delivery with high quality and security.

What was the impact of the AI solution?

Achieved 20% to 30% faster feature development and code implementation. Improved unit test generation by 10% to 30%, reducing bugs and enhancing software quality. Reduced junior developer onboarding time significantly from months to weeks. Scaled AI deployment to 3,000 developers supporting ongoing innovation in code quality and security. Improved developer productivity and accelerated secure software delivery.

Source

GCP

Palo Alto Networks Enhances Developer Productivity with Claude Models on Google Cloud Vertex AI

Use case typeCode assistantUpdated Jun 13, 2026

Palo Alto Networks deployed Anthropic's Claude large language models on Google Cloud's Vertex AI to enhance developer productivity and code quality while maintaining security compliance. Claude models are integrated into IDEs to assist with pair programming, code completion, and post-processing code reviews, accelerating feature development and improving unit test generation. The solution enabled faster onboarding of junior developers from months to weeks and helped senior developers debug code and brainstorm architectural solutions. The deployment has scaled up to 3,000 developers with measurable improvements in speed, security, and code quality, and ongoing efforts to leverage AI for automated code enhancement and security vulnerability patches.

Organization: Palo Alto Networks
Industry: Tech & Comms
Location: United States

Reported outcomes

−30%

timeTime & speed

−20%time+10%quantified impact+30%quantified impact

Strategic outcomes

Speed & agilityAccelerated feature development and implementationNew product / capabilityImproved automated unit test generationEmployee experienceReduced developer onboarding timeScale & capacityScaled AI tools to thousands of developers

Catalog median for time & speed deployments: −60% across 727 reported metrics. Compare benchmarks →

Primary read

Use case focus

Showing 3 of 3

1AI-assisted software development
2Code completion and review
3Developer productivity enhancement

Palo Alto Networks needed to boost software developer productivity and code quality while ensuring strict security compliance across its complex codebases.
Traditional onboarding and code review processes were time-consuming and resource-intensive, limiting developer efficiency.
There was a need for scalable AI-driven tools integrated into the development lifecycle to accelerate software delivery with high quality and security.

Deployed Anthropic Claude models on Google Cloud Vertex AI with secure and performant infrastructure ensuring compliance policies and consistent availability.
Integrated Claude models via IDE plugins provided by Sourcegraph for seamless developer interaction.
Used Claude 3.5 Haiku for code completion and Claude 3.5 Sonnet for pair programming to assist with bug fixes, code improvements, and architectural brainstorming.
Implemented AI-driven post-processing of code including variable renaming, comment generation, unit test creation, and security vulnerability identification and patching.

Technologies

Vertex AI Anthropic Claude models Claude 3.5 Sonnet Claude 3.5 Haiku

Achieved 20% to 30% faster feature development and code implementation.
Improved unit test generation by 10% to 30%, reducing bugs and enhancing software quality.
Reduced junior developer onboarding time significantly from months to weeks.
Scaled AI deployment to 3,000 developers supporting ongoing innovation in code quality and security.
Improved developer productivity and accelerated secure software delivery.