DevSecOps for AI
Secure AI from Code to Deploy
As AI and ML become foundational to modern software development, their security must be as agile and integrated as the models themselves. Wabbi enables secure AI development by embedding security into every step of your MLOps and SDLC—so your models aren’t just smart, they’re secure by design.
Core Benefits
Secure AI/ML Code & Pipelines
Policy-Based AI Governance
Enforce internal and external compliance standards in model development and deployment.
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Protect Training Data & Models
AI moves fast—but security has to keep up. Wabbi’s platform extends DevSecOps to the world of AI , ensuring the models you build are not only performant but protected. From data to deployment, our platform helps teams bake security into the AI pipeline—so you don’t just innovate quickly, you do it safely.
How It Works
Step 1
Integrate Wabbi into your AI/ML workflows—from code to deployment.
Step 2
Apply centralized security policies across data ingestion, model training, and model release.
Step 3
Track and manage vulnerabilities and misconfigurations in AI-specific components.
Step 4
Automatically enforce controls around sensitive data use and model drift.
For Who
For Developers
Build AI securely with clear policies embedded directly into your workflow—no second-guessing.
For Security Teams
Easily deploy and enforce AI-specific policies across pipelines—no manual effort, no slowdowns.
For CISOs
Adopt AI in development without adding risk—by aligning with your existing security and compliance frameworks.
Testimonials
As we accelerated GenAI adoption, Wabbi gave us a secure foundation that let us scale without fear.”
Wabbi helped us embed governance into every stage of our AI lifecycle, which made our CISO and our data science teams equally happy.”
