New release integrates automated security scanning, AI-powered remediation, and GitHub-native workflows for enterprise development teams.
Pervaziv AI today announced the release of AI Code Review 2.0, a new GitHub Action designed to automate repository-wide security scanning while integrating directly into developer workflows.
The release expands the capabilities of the company’s AI Code Review platform, following the launch of AI Code Review 1.0, a GitHub App introduced on the GitHub Marketplace on February 13, 2026.
Together, the two products create a unified DevSecOps workflow that combines AI-powered code review, automated vulnerability detection, and developer-friendly remediation directly within GitHub. The new GitHub Action is bundled with Pervaziv AI’s DevSecOps Suite version 2.8 and is available to organizations using Premium and higher subscription tiers.
Addressing Enterprise DevSecOps Workflow Challenges
Modern software development teams often face fragmented security workflows that require switching between multiple tools for code scanning, vulnerability management, and remediation.
Pervaziv AI developed AI Code Review 2.0 to reduce that friction by bringing security insights directly into GitHub while still providing deeper analysis in its DevSecOps platform.
The GitHub Action scans the entire repository for vulnerabilities and publishes results within GitHub Actions and the Security tab, while generating a comprehensive security report inside the Pervaziv AI DevSecOps Console.
“Security should not slow down development,” said Anoop Jaishankar, Founder and CEO of Pervaziv AI. “Our goal with AI Code Review 2.0 is to bring intelligent security insights directly into developer workflows while giving security teams the deeper analysis they need to manage risk across the entire codebase.”
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Built from Real Developer and Security Team Insights
Following the launch of AI Code Review 1.0 earlier this year, Pervaziv AI analyzed how enterprise developers and security analysts interacted with code security tools within its DevSecOps platform.
Using analytics and telemetry from the Pervaziv AI DevSecOps Console, the company studied common pain points in code review and vulnerability management workflows. These insights guided the development of AI Code Review 2.0, which focuses on simplifying security operations while minimizing context switching for developers.
The result is a GitHub-native security automation workflow that combines continuous scanning, AI-powered remediation suggestions, and integrated reporting.
Key Capabilities of AI Code Review 2.0
The new GitHub Action introduces several capabilities designed for enterprise development environments:
– Automated GitHub Security Scanning
— Run repository-wide security scans directly within GitHub using automated workflows.
– Integrated Workflow Feedback
— View execution status and scan results within the GitHub Actions interface.
– Full Repository Security Analysis
— Identify vulnerabilities across all files within a repository.
– Generative AI Code Fixes
— Integrates with Pervaziv AI’s AI Code Review engine to generate remediation suggestions using generative AI.
– DevSecOps Console Integration
— Access comprehensive reports, vulnerability rankings, and remediation insights within the Pervaziv AI DevSecOps Console.
Benefits for Development and Security Teams
AI Code Review 2.0 expands the benefits of the original GitHub App while improving automation, visibility, and scalability for organizations managing complex software systems.
Key benefits include:
– Continuous Code Security
— Repositories can be scanned automatically on every push or scheduled interval, ensuring vulnerabilities are detected early in the development lifecycle.
– Security Metrics and Reporting
— Detailed vulnerability reports provide key security metrics across all files in a repository, enabling better risk prioritization.
– Streamlined Debugging
— Automated analysis reduces the need for manual code review, allowing developers to focus on building features while security issues are flagged automatically.
– Knowledge Base Integration
— The platform can query both public and private knowledge bases to enrich vulnerability analysis and remediation guidance.
– Scalability Across Large Codebases
— AI Code Review supports more than 15 programming languages and can analyze large enterprise repositories.
– Generative AI Security Enhancements
— Security scanning, vulnerability detection, and remediation suggestions are enhanced using Pervaziv-LLM, the company’s AI model designed to provide contextual code insights and recommendations.
Combining GitHub-Native Automation with AI Security Intelligence
The combined architecture of AI Code Review 1.0 and 2.0 enables organizations to implement a layered code security workflow.
AI Code Review 1.0 GitHub App
Operates during pull requests to analyze code changes and provide AI-generated remediation suggestions.
AI Code Review 2.0 GitHub Action
Runs across entire repositories to detect vulnerabilities and publish results directly into GitHub security workflows.
Together, these tools enable development and security teams to detect vulnerabilities earlier and resolve them faster.
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