AI-Powered Policy Creation, Optimization, and Testing — All in One Place

We’re transforming how security policies are written, tested, and maintained. With the powerful combination of Policy Playground and Policy Optimizer, security teams now have an end-to-end environment to create accurate, AI-enhanced security policies that detect real issues while minimizing noise.

The Policy Playground is an interactive development environment that gives teams a split-screen interface: one side for writing or editing policies, the other for viewing how those policies match real code. This real-time feedback loop drastically reduces iteration cycles, allowing teams to see the impact of their changes instantly—whether it's catching a known vulnerability or preventing a false positive. With support for detection, false positive suppression, and fix generation policies, teams can test everything before deployment.

But writing great policies isn’t just about testing—it’s about precision. That’s where the Policy Optimizer comes in. Using advanced AI models, the Optimizer takes basic policy logic and automatically enhances it with:

• Language-specific vulnerability patterns

• Aligned CWE mappings

• Clear remediation guidance

• False positive filters

All while preserving your original security intent and context.

Key benefits of combining the two:

• Faster development: Build and refine policies in minutes, not hours

• More accurate scanning: Optimized rules that detect real issues while avoiding false alarms

• Standards compliance: Policies enhanced with CWE alignment and best practices

• Team enablement: A collaborative, intuitive workspace that simplifies policy creation

• Scalability: Consistent, reusable policies that grow with your codebase and team

Whether you're building new policies from scratch or refining existing ones, the Policy Playground and Optimizer together create a seamless workflow—from drafting, to testing, to optimizing. It's the new standard for modern AppSec teams who want both speed and precision.