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LangGuard vs Noma Security

The deterministic AI governance control plane vs. AI security posture & detection — compared on 12 governance & compliance criteria for enterprises putting AI agents into production.

Strong / documented Partial / indirect Absent / not publicly documented

LangGuard

Deterministic runtime AI governance control plane

LangGuard is a deterministic runtime AI governance control plane. Two engines work across the full agent lifecycle: SCOPE-MCP maps and compliance-classifies an agent's action surface before it ships, and Arbiter deterministically authorizes every agent action before it executes — clearing safe actions with no added latency and routing anything that crosses a Segregation-of-Duties boundary or policy threshold to a named approver. The authorization is the governance; the audit trail is automatic.

Noma Security

AI security platform (AI-SPM + AI-DR + red teaming)

Noma is a broad AI security platform — AI security posture management (model, pipeline and notebook scanning), AI detection & response, agentic access control, and automated red-teaming — across 80+ data and AI platforms. The most heavily funded vendor in this set.

How they compare

Twelve criteria that decide whether an enterprise can prove — not just hope — that its AI agents stay inside policy.

Criterion LangGuard Noma
Deterministic, rule-based authorization
Pre-execution enforcement
Segregation of Duties enforcement
Excessive-agency prevention / least privilege
Design-time action-surface mapping
Compliance-classified tools catalog
Full lifecycle coverage (design-time + runtime)
Named-approver human-in-the-loop routing
SOX / GDPR / financial-GRC control mapping & evidence
AI-specific standards (ISO 42001, EU AI Act, NIST AI RMF, OWASP LLM)
Immutable / tamper-evident audit ledger
GRC / internal-audit / IT-governance buyer fit

Where Noma Security is strong

  • Deep AI-SPM and AI supply-chain security — model artifacts, serialization risks, pipelines, notebooks
  • ML-based threat detection for prompt injection and data leakage, with sensitive-data masking
  • Automated red-teaming and broad discovery across 80+ data/AI platforms
  • Maps to OWASP LLM, MITRE ATLAS, NIST AI RMF, EU AI Act and ISO 42001 — the standards leader here

Where LangGuard pulls ahead

  • Enforcement is detection-led and probabilistic, not deterministic pre-execution authorization
  • No Segregation-of-Duties enforcement
  • Framework mapping is AI-security-standard-centric — no SOX or GDPR financial-GRC evidence
  • Approvals are a security-review queue, not routing to named business approvers
  • Audit logging is present but not positioned as tamper-evident; AppSec/SecOps buyer, not GRC

The bottom line

Noma Security is a capable ai security posture & detection. But securing how an agent operates is not the same as governing what it is allowed to do. LangGuard makes a deterministic, rule-based authorization decision on every action before it executes — enforcing Segregation of Duties, routing risky actions to named approvers, and emitting audit-grade SOX/GDPR evidence. It is the governance control plane that sits above the layer Noma Security operates in.

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