Noma Security vs WitnessAI (2026): AI Security Compared — and Where Kosmoy Fits

Three shapes on the same ten axes. Noma Security (orange) and WitnessAI (violet) both peak on Security and Guardrails and both document self-hosted/hybrid deployment. They diverge on emphasis: Noma reaches further on Testing & Red-teaming and Agent Containment (posture, adaptive red teaming, connection-level blocking), while WitnessAI leads on Compliance & Audit (trails mapped to EU AI Act, ISO 42001, NIST and PCI) and network-level Gateway enforcement. Both sit low on FinOps and Agent Building. Kosmoy (blue) spans the wider web and, decisively, kernel-enforced Agent Containment. Read it as area: the specialists own detection and policy; the suite adds contained execution.

Buildtime posture and adaptive red teaming. Noma assesses agent configurations before deployment and runs an agent-based, CI/CD-embedded red-team engine (Nemotron-powered as of May 2026). WitnessAI's coverage starts at runtime traffic, with no buildtime posture assessment documented as of July 15, 2026.

Agent containment actions. Agent Access Control gives each agent a distinct identity and blocks disallowed agents, MCP servers or tools from connecting. WitnessAI observes agent activity and shields it from malicious prompts, but documents no agent containment, sandboxing or scoped-credential mechanism — monitoring, not containment.

Depth on the AI supply chain. AISPM covers malicious models, poisoned data and misconfigurations for the AI you build — a layer WitnessAI's employee-use focus does not target.

Shadow-AI visibility of employee AI use. Network-level cataloging sees native desktop apps, IDEs and API-driven agents without endpoint clients — the employee shadow-AI problem Noma's homegrown-AI focus does not aim at.

Intent-based enforcement and tokenization. Allow/warn/block/route/redact by role, department and intent, plus real-time tokenization that keeps PII and credentials inside the enterprise while employees use external AI.

Compliance-grade audit trails. Immutable audit trails explicitly mapped to EU AI Act, ISO/IEC 42001, NIST AI RMF and PCI DSS 4.0.1, with multi-region data residency — a deeper compliance-reporting posture than Noma's security-centric governance.

Noma and WitnessAI attack different halves of AI security — Noma the AI you build, WitnessAI the AI your people use — and both do their half well. But look at what happens to an agent once it is running. WitnessAI observes agent activity and blocks malicious prompts before they reach the agent; its documentation shows no sandboxing, kill switch or scoped-credential mechanism. Noma goes further — per-agent identity and connection-level blocking — but still runs no sandboxed execution environment. Neither holds an agent inside a runtime it cannot escape.

Kosmoy answers that with architecture. Every agent runs inside an Action Capsule — a kernel-enforced sandbox whose only egress is its paired gateway, with per-task credentials and a live kill switch — so containment does not depend on detecting the attack first. Around it sit the layers these specialists leave out: an org-wide inventory with a master agent registry (Foundry, Bedrock, Vertex, Salesforce, ServiceNow) and EU AI Act, ISO 42001 (aligned) and NIST AI RMF evidence generated from registry state and gateway logs.

The honest framing: WitnessAI out-covers Kosmoy on employee shadow-AI and audit-trail breadth, and Noma out-red-teams it. Detection, policy and red teaming are spokes. If the requirement is to contain every agent by default and prove control over all your AI in your own infrastructure, that is a suite decision — the kind Kosmoy runs air-gapped for Banca d'Italia (Italy's central bank and banking regulator) and Leonardo (Europe's largest defence and aerospace group).

For a team whose problem is one specific half of AI security, pick accordingly: Noma to secure the AI you build (posture, red teaming, agent identity), WitnessAI to govern the AI your people use (shadow-AI visibility, intent-based policy, tokenization, audit trails). They overlap little, and some enterprises run both.

For an enterprise that must contain agents by default and prove control over all of its AI on its own infrastructure, the decision is between detection-and-policy specialists and a control plane. A common pattern: WitnessAI for employee AI governance, Noma for homegrown-AI posture, and Kosmoy for contained execution, inventory and compliance evidence.