The Platform

AI-native and traditional. One platform.

Most vendors bolt AI onto a legacy scanner — or sell you a chatbot without the foundational coverage your auditors need. Safeguard does both, on a single architecture, with one policy engine and one workflow surface.

Architecture deep-dive

Two halves. Shared everything.

AI-Native

Reasoning & the agent era

  • Griffin AI (reachability + fix)
  • MCP Server governance
  • Guardrails (prompt-injection defense)
  • AI-BOM
  • Auto-Fix
  • Zero-day eval harness
Explore AI-native track
Traditional

Foundational AppSec & supply chain

  • SCA
  • SBOM Studio
  • IaC Security
  • DAST
  • Secure Containers
  • Secret Detection
  • TPRM
  • Scanner Suite
Explore foundational track

Five layers. Single architecture.

Why findings, fix PRs, and evidence stay coherent across every product.

1. Unified ingest

Repos, registries, IaC, runtime, third-party SBOMs, MCP servers, AI agents — one normalized graph of every asset and dependency.

2. Griffin AI reasoning

Reachability, fix synthesis, zero-day eval, and AI-agent intent inference run continuously over the graph.

3. One policy engine

Policy-as-code across SCA, IaC, DAST, AI agents, and TPRM. Same gate logic in PRs, deploys, runtime, and procurement.

4. Single workflow surface

One PR check, one dashboard, one ticketing integration. Findings, fix PRs, evidence and exceptions all live together.

5. Evidence store

Continuous SBOM, VEX, scan logs, policy violations and attestations — exportable as framework-mapped audit packs.

Deploy where your data lives.

SaaS

Multi-tenant. Up and running in under an hour.

Private cloud

Dedicated VPC in your AWS / GCP / Azure account.

Sovereign / air-gapped

Self-hosted with full model weights — runs disconnected.

See the platform on your stack.