PARTNERS

Embed, resell, or white-label AI security — OEM, scanner, MSSP, consulting, and reseller tracks are open now

Commercial / Deployment

Choose the deployment model that matches the data boundary.

AI security can run as SaaS, local worker, private worker, OEM sidecar, hybrid, offline, or air-gapped depending on customer and partner constraints.

CLI
Headless invocation for partners and automation
SARIF
Scanner-friendly output for partner ingestion
OEM
Commercial path for embedded AI security coverage
Deployment

Keep sensitive work where it belongs

The strongest architecture gives each buyer the right boundary: SaaS for control, local worker for privacy, sidecar for OEM, and air-gap for sensitive environments.

SaaS

Platform-Controlled SaaS

The AI Security LLC platform governs identity, organizations, credits, entitlements, usage, artifacts, and reports.

  • Best for direct customers and managed commercial programs
  • Centralized billing and entitlement decisions
  • Fastest path to procurement-ready evidence workflows
Local worker

Desktop or CLI Worker

Local execution for code, repository, proxy, and evidence workflows with platform-controlled licensing and usage sync.

  • Keeps sensitive repositories and traces local
  • Supports offline cache and queued usage
  • Appropriate for enterprise and consultant delivery
OEM

Embedded Sidecar

A headless binary or localhost service that a partner product invokes and ingests as native scanner output.

  • Best for scanner providers and platforms
  • No partner UI dependency on AI Security LLC
  • Supports co-branded, private-label, and white-label packaging
Private

Air-Gapped or Offline

Disconnected deployment for sensitive environments with signed license grants, hard-capped usage, and controlled update channels.

  • No continuous internet dependency
  • Explicit scope, expiry, and capability limits
  • Suitable for high-sensitivity enterprise programs

Build the right commercial path

Use a focused pilot to align the technical integration, licensing structure, support model, and customer-facing packaging.