Enterprise
Governance, AI security, and scale for multi-team organizations
For multi-team organizations needing governance, AI security, and scale.
What's included
- Everything in Scale, enterprise-wide
- Secure AI SDLC and agentic AI security engineering
- Enterprise AI coding governance and advanced validation
- Security champions program operation
- Architecture board support and program-level threat modeling
- Dedicated Secure Engineering pod model
- Executive dashboard and quarterly + annual maturity roadmap
- Cross-pillar alignment with Protect & Monitor and Advisory
Included services
Implement secure software development lifecycle practices
View serviceSetup and integrate security into DevOps pipelines
View serviceIntegrate security testing and checks into CI/CD pipelines for automated security feedback
View serviceSecure dependencies, SBOM, provenance, signing, and build integrity across the software supply chain
View serviceHarden infrastructure-as-code and container build pipelines with policy-as-code and image security controls
View serviceValidate AI-generated code and secure AI-assisted development workflows with expert-led, AI-augmented review
View serviceDefine policies and guardrails for safe use of AI coding tools across engineering teams
View serviceDesign and build secure LLM, RAG, and AI systems from the start with AI-specific engineering controls
View serviceSecure autonomous AI agents, tool-calling, and MCP integrations with permission models and action approval workflows
View serviceEmbed and scale secure engineering practices inside development teams through a structured security champions program
View serviceDedicated secure engineering pod delivering ongoing SDLC, DevSecOps, supply-chain, and AI-native development security on a managed program basis
View serviceEstablish application security governance framework, policies, and processes
View serviceManaged continuous application security program
View servicePackage comparison
| Capability | Launch | Scale | Enterprise |
|---|---|---|---|
| Secure SDLC baseline | Included | Included | Enterprise-wide |
| Architecture review | Light | Priority systems | Architecture board support |
| Threat modeling | Light | Product-level | Program-level |
| Secure code review process | Basic | Full workflow | Enterprise standard |
| Developer security enablement | Basic | Role-based | Champions + continuous enablement |
| DevSecOps setup | Basic | Advanced | Enterprise standard |
| CI/CD pipeline security | Basic | Advanced | Enterprise policy |
| Software supply chain security | Basic | Included | Full governance |
| AI-assisted development security | Optional | Included | Advanced |
| AI coding policy | Basic | Included | Enterprise governance |
| Secure AI SDLC | Optional | Optional | Included |
| Security champions | Intro | Program design | Program operation |
| Secure Engineering as a Service | Optional | Retainer | Dedicated model |
| Reporting | Summary | Monthly dashboard | Executive dashboard |
| Maturity review | Optional | Quarterly | Quarterly + annual roadmap |
Good fit if you
- Regulated enterprises with portfolio-wide AppSec mandates
- Organizations building AI-native products (LLM, RAG, agents)
- Multi-team orgs needing executive reporting and governance evidence
Not included (consider upgrading)
- Public cloud infrastructure pentest (available as Assess&Pentest add-on)
Typical scope for Enterprise
Enterprise fits multi-team portfolios with governance, compliance evidence, AI product security, and a dedicated secure engineering operating model.
Typical: 20+ applications (portfolio-wide)
Typical: 50+ repositories
Typical: 150+ developers across business units
Typical: 25+ CI/CD pipelines
Typical: LLM, RAG, or agentic products in production
Typical: Audit-ready evidence and executive reporting
Typical: Dedicated pod + executive governance
What affects pricing
We do not publish fixed prices. Your proposal depends on scope and complexity.
Number of developers, squads, and products in scope affects enablement depth and coaching cadence.
More repos and apps require broader toolchain integration and governance models.
Platform choice, number of pipelines, and release frequency drive DevSecOps and release security effort.
Use of AI coding tools and AI-powered products determines AI governance and secure AI SDLC depth.
Regulated industries and audit cycles increase reporting, evidence packs, and maturity program scope.
One-time setup vs ongoing retainer vs dedicated pod — each maps to a different commercial structure.
Contact us for a tailored proposal based on your engineering context.
Extend your package
Extend your Build Secure package with specialized services.