Enterprise

Implement secure software development lifecycle practices

Setup and integrate security into DevOps pipelines

Integrate security testing and checks into CI/CD pipelines for automated security feedback

Secure dependencies, SBOM, provenance, signing, and build integrity across the software supply chain

Harden infrastructure-as-code and container build pipelines with policy-as-code and image security controls

Validate AI-generated code and secure AI-assisted development workflows with expert-led, AI-augmented review

Define policies and guardrails for safe use of AI coding tools across engineering teams

Design and build secure LLM, RAG, and AI systems from the start with AI-specific engineering controls

Secure autonomous AI agents, tool-calling, and MCP integrations with permission models and action approval workflows

Embed and scale secure engineering practices inside development teams through a structured security champions program

Dedicated secure engineering pod delivering ongoing SDLC, DevSecOps, supply-chain, and AI-native development security on a managed program basis

Establish application security governance framework, policies, and processes

Managed continuous application security program