Best AI Security Platforms in 2026: 6 Compared
AI security in 2026 spans shadow-AI discovery, runtime threat detection, red teaming and agent containment. Almost everyone can detect and validate agents; very few can sandbox one. This guide scores containment strictly and organizes the field by buyer type.
AI security hardened into a real category in 2026, and the money followed. Palo Alto Networks assembled Prisma AIRS from three acquisitions — Protect AI, Koi Security and Portkey; Cisco followed its Robust Intelligence deal by acquiring Astrix Security (a reported ~$400M, May 2026) to bolster agent identity; WitnessAI raised $58M and extended into agentic control; Noma Security closed a $100M Series B; and Gartner tagged both Zenity and Palo Alto as a 'Company to Beat' in AI security. Prompt Security (now part of SentinelOne) and Lakera (now part of Check Point) press on the same problem from adjacent corners.
This guide compares six platforms enterprises actually shortlist to secure AI apps, models and — increasingly — autonomous agents. It scores them on shadow-AI discovery, runtime threat detection, red teaming and containment, and it draws one line hard: detection is close to a solved problem, but containment is not. Almost every vendor here can find an agent, score its posture and block behavior it can see. Very few can put an agent inside a runtime it physically cannot escape. Kosmoy publishes this page; where the security specialists out-detect and out-red-team it, we say so plainly, and Kosmoy earns its place on exactly one axis — enforced containment.
What counts as AI security platforms in 2026
An AI security platform in 2026 answers four questions with tooling. What AI do we run, sanctioned or not? — discovery of apps, models, MCP servers and agents, including the shadow AI nobody registered. Is it configured safely? — posture management and model scanning. What is happening at runtime? — detection and blocking of prompt injection, data exfiltration, unsafe output and tool misuse. And what happens when an agent is compromised? — the containment question, where the market quietly divides.
Most vendors answer the fourth question with detection and response: alert, revoke a permission, quarantine a workload, block a connection, assign a scoped identity. Those are real controls, and for many estates they are enough — but they act on an agent that is still running in a shared environment, after it has done something observable. Containment is the stricter property: the agent executes inside an isolated runtime and physically cannot reach systems outside its allowed surface. We score that axis strictly. In this set of six, the only true agent sandbox for arbitrary frameworks is Kosmoy's Action Capsule; Cisco ships a sandbox (open-source DefenseClaw) scoped to the OpenClaw runtime; Prisma AIRS enforces scoped identity and gateway policy but does not isolate execution; Zenity and Noma quarantine and block connections; WitnessAI observes and shields but does not sandbox. Monitoring an agent is not containing it.
The category is consolidating around bigger balance sheets, and buyers now weigh venture-backed specialists (Zenity, Noma, WitnessAI) against platform giants attaching AI security to estates they already own (Palo Alto, Cisco). Several notable capabilities are no longer sold standalone: Robust Intelligence's AI validation and 'AI Firewall' now live inside Cisco AI Defense, and Protect AI's model scanning inside Prisma AIRS. Adjacent tools worth knowing but not profiled here — HiddenLayer for model scanning and detection-and-response, Prompt Security (SentinelOne) and Lakera (Check Point) for prompt-level runtime protection — cover slices of this surface but not the containment axis this guide weights most heavily.
How we scored the field
Every product is scored 0–10 on the same ten capability axes. A 10 is reserved for categorical architectural facts; specialists are expected to outscore platforms on their own spoke, and the scores show it.
AI Inventory & Discovery
Discovery of every AI app, model, MCP server and agent in the organization — including shadow AI and agents built on third-party platforms — surfaced in one place with owners.
Security & Shadow AI
Shadow-AI detection, posture management of AI/agent configurations, model scanning, and runtime threat detection (prompt injection, data exfiltration, tool misuse) — the core of the category.
Guardrails & Runtime Safety
In-line blocking at runtime — prompt injection, PII leakage, toxic content, unsafe output — scored on whether it blocks synchronously, not only logs.
Agent Containment
Scored strictly: sandboxed execution, scoped per-task credentials and a kill switch. Scoped identity, quarantine and connection blocking score mid; monitoring alone scores near zero.
Testing, Evals & Red-teaming
Adversarial testing and red teaming of models and agents — adaptive, multi-turn, multilingual attacks — before and after deployment, not static checklists.
Deployment Sovereignty
Where the security control plane runs and what the vendor sees. SaaS-only scores low; self-hosted and air-gap-capable score high; the top score is reserved for no vendor control plane at all.
The field, scored
| Capability (0–10) | Kosmoy | Cisco AI Defense | Palo Alto Prisma AIRS | Zenity | Noma Security | WitnessAI |
|---|---|---|---|---|---|---|
| AI Inventory & Discovery | 9 | 8 | 8 | 9 | 9 | 8 |
| Security & Shadow AI | 8 | 9 | 9 | 9 | 9 | 9 |
| Observability & FinOps | 7 | 4 | 6 | 5 | 4 | 5 |
| Gateway & Policy Control | 8 | 7 | 7 | 5 | 6 | 7 |
| Guardrails & Runtime Safety | 8 | 8 | 8 | 8 | 8 | 8 |
| Agent Containment | 9 | 7 | 5 | 6 | 6 | 2 |
| Compliance & Audit | 9 | 5 | 5 | 6 | 5 | 7 |
| Testing, Evals & Red-teaming | 4 | 8 | 8 | 3 | 8 | 4 |
| Agent Building | 6 | 1 | 1 | 0 | 0 | 0 |
| Deployment Sovereignty | 10 | 4 | 4 | 2 | 8 | 7 |
Bold marks the highest score on each row. 10 is reserved for categorical architectural facts; specialists are expected to outscore platforms on their own spoke.
Capability shape, vendor by vendor
Each panel shows one vendor across the same ten axes. Read it as area: a specialist climbs on its own spoke and falls away on the rest; a platform holds the frontier. The dashed outline is Kosmoy for reference.
The vendors, by buyer type
No single 1-to-N ranking survives contact with a real shortlist — the right pick depends on who is buying. Each vendor below is labeled with the buyer it fits best.
Kosmoy
AI management platformBest for kernel-enforced agent containment and sovereignty
A self-hosted control plane for enterprise AI: one inventory, one policy gateway, one audit trail and a containment sandbox for every model, agent and MCP server a company runs.
Kosmoy treats AI security as an architecture problem, and its distinctive capability is the one most of this field lacks: enforced containment. Every agent, model or MCP server runs inside an Action Capsule — a Docker container plus an in-container sandbox built on kernel primitives (namespaces, cgroups v2, Seccomp, Landlock, AppArmor/SELinux) with default-deny L3/L4 egress, an in-pod L7 allow-list proxy, the paired gateway as the only door out, and a live kill switch from Mission Control. On the discovery side, its master agent registry harvests agent inventories from Azure AI Foundry, AWS Bedrock, Google Vertex AI, Salesforce and ServiceNow and flags what nobody registered as shadow AI. Guardrails run in the gateway path (PII, toxicity, prompt-injection defence), and the whole platform runs single-tenant in your own Kubernetes, air-gapped if needed — in production at Italy's central bank and banking regulator and Europe's largest defence and aerospace group.
The honest concessions: the security specialists out-detect it. Kosmoy has no posture-management engine, no model-scanning line and no adaptive red-teaming suite, so teams pair it with a Zenity, Noma, Cisco or Palo Alto for AISPM, validation and testing. Kosmoy's win is narrow and real — it makes unauthorized reach architecturally impossible and keeps the control plane in your perimeter — not that it is the broadest AI security tool on the page.
Strengths
- Four registries — AI systems, models, MCP servers and a master agent registry that pulls agents from Azure AI Foundry, Bedrock, Vertex, Salesforce and ServiceNow into one list.
- One OpenAI-compatible gateway enforcing guardrails, RBAC, budgets and logging on every LLM, MCP and A2A call.
- Action Capsule: kernel-enforced sandboxing for agents, MCP servers and private models, with per-task credentials and a kill switch.
Limits
- No dedicated evaluation or red-teaming suite — teams pair Kosmoy with a specialist evals tool.
- The agent builder covers governed internal use cases; dedicated agent-development platforms go deeper.
- No free or self-service tier — procurement runs through an enterprise sales process.
Cisco AI Defense
Enterprise AI security suite embedded in a network-security portfolioBest network-scale AI security for Cisco estates
Cisco AI Defense (built on the Robust Intelligence acquisition) combines employee AI-access control, AI asset discovery across clouds, algorithmic model validation and network-enforced runtime guardrails, expanded through 2026 to agentic/MCP governance and open-source agent sandboxing (DefenseClaw).
Cisco moved fast on agentic security: an AI BOM, an MCP Catalog and in-path MCP policy control landed in February 2026, agent zero-trust IAM via Duo in March 2026 (reinforced by the Astrix Security acquisition), and the Robust Intelligence heritage supplies genuinely strong, adaptive multi-turn, multilingual algorithmic red teaming (agentic-era expansion). DefenseClaw, its open-source governance framework, is the only shipping agent sandbox in this set besides Kosmoy's — admission control plus OpenShell network/filesystem/syscall isolation.
The caveats: DefenseClaw's sandbox is scoped to the OpenClaw runtime, not arbitrary agent frameworks; the strongest value assumes the broader Cisco stack (Secure Access, Hypershield); and the management plane is Cisco SaaS with no self-hosted control plane or EU AI Act / ISO 42001 evidence automation documented as of July 15, 2026.
Strengths
- Top-tier model validation and algorithmic red-teaming pedigree via the Robust Intelligence acquisition, continuously updated by Cisco-scale threat research (model validation).
- Enforcement fused into network infrastructure the enterprise already owns — Secure Access SSE, Hypershield eBPF enforcement points, switches — so guardrails apply without app code changes (Hypershield overview).
- Moved fastest among large vendors on agentic/MCP governance: AI BOM, MCP Catalog and in-path MCP policy control (February 2026), plus agent zero-trust IAM via Duo and Identity Intelligence (March 2026) (expansion announcement).
Limits
- Strongest value requires the broader Cisco stack (Secure Access, Hypershield, Duo, Identity Intelligence) — the standalone footprint is narrower.
- Sandboxing and containment (DefenseClaw/OpenShell) are currently scoped to the OpenClaw agent runtime, not arbitrary enterprise agent frameworks.
- No EU AI Act, ISO/IEC 42001 or NIST AI RMF compliance-evidence automation documented as of July 15, 2026.
Palo Alto Prisma AIRS
Enterprise AI security platform (model scanning, posture, red teaming, runtime and agent security) from a top-tier network-security vendorBest widest AI security surface from a platform giant
Prisma AIRS is Palo Alto Networks' AI security platform spanning AI Model Security, AI Posture Management, AI Red Teaming, AI Runtime Security and AI Agent Security, assembled by folding in the Protect AI, Koi and Portkey acquisitions.
Prisma AIRS is the broadest AI security surface among large vendors, assembled from acquisitions: Protect AI model scanning (~$634.5M), Koi Security's agentic endpoint security ($231M) and, from May 2026, Portkey's high-throughput gateway (completed acquisition). It spans five capabilities — model security, posture management, red teaming, runtime security and agent security — and its AI Runtime Security blocks 30+ prompt-injection and jailbreak techniques and scans 1,000+ sensitive-data patterns in real time. Prisma AIRS 3.0 (March 2026) added agent discovery, artifact scanning, governed agent identity and an AI Agent Gateway (3.0 launch); Palo Alto reports being named a 'Company to Beat' in AI security for a second year.
The caveats are maturity and sovereignty. The AI Agent Gateway is in limited preview and the Portkey acquisition only closed May 29, 2026, so end-to-end integration is unproven; containment is scoped identity plus gateway policy, not sandboxed execution; and it is SaaS-centric — a self-hosted or air-gapped control plane is not documented as of July 15, 2026, despite Portkey's air-gap heritage.
Strengths
- Widest AI-security surface among large vendors — model scanning, posture management, red teaming, runtime protection and agent security — assembled by folding in Protect AI, Koi and Portkey (Prisma AIRS 3.0).
- Prisma AIRS 3.0 (March 2026) moves from observing AI to authorizing autonomous execution: agent discovery across cloud, SaaS and endpoints, agent artifact scanning, governed agent identity with scoped permissions and audit trail, and an AI Agent Gateway control plane (3.0 launch).
- The Portkey acquisition (closed May 29, 2026) folds in a production AI gateway that had been routing to 250+ LLMs, giving Prisma AIRS runtime traffic control plus observability that pure detection tools lack (Portkey acquisition).
Limits
- Primarily SaaS (Strata Cloud Manager control plane); Palo Alto does not document a self-hosted or air-gapped Prisma AIRS control plane as of July 15, 2026, and Portkey's air-gapped heritage is not yet offered as a Prisma AIRS option.
- Key agentic pieces are newly acquired or in limited preview — the AI Agent Gateway is described as limited preview and the Portkey acquisition only closed in May 2026 — so end-to-end integration maturity is still unproven.
- Containment is scoped agent identity plus gateway policy enforcement, not sandboxed or isolated execution; no runtime agent-isolation environment is documented as of July 15, 2026.
Zenity
AI agent security & governance platform (AISPM + AIDR)Best for copilot and low-code agent security
Zenity is a SaaS security and governance platform purpose-built for enterprise AI agents and copilots — automatic discovery, posture management (AISPM) and runtime detection & response (AIDR) across Copilot Studio, Power Platform, M365 Copilot, ChatGPT Enterprise and homegrown agents.
Zenity has the broadest documented coverage of business-platform agents — Copilot Studio, Power Platform, M365 Copilot, ChatGPT Enterprise, Azure AI Foundry, homegrown and endpoint agents — spanning discovery (Observe), posture (AISPM) and runtime detection and response (AIDR). Its inline, step-level prevention inside Copilot Studio agents reached GA in November 2025, deeper than the API-log monitoring most rivals offer, and Gartner's 'Company to Beat' label reflects genuine category leadership (inline prevention GA).
Its response actions — quarantine, permission revocation, execution blocking — are real but stop short of a sandboxed runtime, the platform is SaaS-only with no self-hosted option documented as of July 15, 2026, and the deepest enforcement is Microsoft-ecosystem specific.
Strengths
- The broadest documented coverage of business-platform agents in the category: Copilot Studio, Power Platform, M365 Copilot, Fabric, ChatGPT Enterprise (via the OpenAI Compliance API), Azure AI Foundry, plus homegrown and endpoint agents (Zenity platform).
- An end-to-end buildtime-to-runtime story — Observe (discovery), AISPM (posture) and AIDR (detection & response) — rather than detection alone (AISPM).
- Inline, step-level prevention inside Microsoft Copilot Studio agents reached GA in November 2025, with Microsoft Foundry in preview — enforcement inside the agent's execution path, deeper than API-log monitoring (announcement).
Limits
- SaaS-only: no self-hosted, customer-VPC or air-gapped deployment documented as of July 15, 2026.
- Containment is response-action based — agent quarantine, permission revocation, execution blocking — with no sandboxed execution environment for agents.
- Deepest (inline) enforcement is Microsoft-ecosystem specific (Copilot Studio GA, Foundry preview); coverage of other stacks is monitoring- and posture-oriented.
Noma Security
Unified AI & agent security platform (discovery, AISPM, red teaming, runtime protection)Best AI security lifecycle with a self-hosted option
Noma Security is an enterprise AI security platform covering discovery, posture management (AISPM), automated red teaming, runtime protection and — since June 2026 — identity-based access control for agents and MCP servers, deployable SaaS or self-hosted.
Noma covers the full lifecycle in one platform — discovery, posture, adaptive CI/CD-embedded red teaming and runtime protection — with posture findings auto-configuring runtime policies. Its Agent Access Control launch (June 2026) added a per-agent identity with approve/review/block states and tool-level access policies for agents and MCP servers (launch). Unusually for the category, SaaS and on-prem/self-hosted deployments are both documented, so security events need not leave the customer environment, and a $100M Series B funds the roadmap.
It is not a gateway (no routing or failover — a Kong plugin fills that), containment is connection-level blocking rather than sandboxed execution, and EU AI Act / ISO 42001 evidence automation is not prominently documented as of July 15, 2026.
Strengths
- One of the best-funded AI-security pure-plays: $132M raised in under two years, including a $100M Series B in July 2025 led by Evolution Equity Partners.
- Full lifecycle in one platform — discovery, posture, red teaming, runtime enforcement — with AISPM risk scores auto-configuring runtime guardrail policies (Runtime Protection).
- Agent Access Control (June 2026): an enterprise agentic registry giving each agent a distinct identity, approve/review/block governance states and tool-level access policies for agents and MCP servers (launch announcement).
Limits
- No sandboxed execution environment for agents — containment is per-agent identity plus connection-level blocking, not runtime isolation.
- Not an LLM gateway: no model routing, provider failover or centralized LLM traffic management (the Kong partnership fills this gap).
- No FinOps or cost observability (token spend, budgets, chargeback) documented as of July 15, 2026.
WitnessAI
Employee & agent AI-use observation and policy enforcement (shadow-AI security)Best for shadow-AI and employee/agent usage at the network level
WitnessAI is a network-level AI security and governance platform that observes how employees and (since January 2026) AI agents use AI apps, enforces intent-based policies — allow, warn, block, route, redact — and defends against prompt attacks at runtime.
WitnessAI watches the traffic layer: every AI app, agent, MCP server and conversation cataloged at network level without endpoint clients, with intent-based policies that allow, warn, block, route or redact by role and department, and real-time tokenization that keeps PII inside the enterprise. Its January 2026 $58M round funded the agentic extension — tracking which agents are active, linking human and agent identities, and blocking attacks before they reach agents (raise and agent security).
It is the strongest pick here for the employee-usage (shadow AI) problem and the weakest on containment: agents are observed and shielded, but there is no sandbox, scoped credential or kill switch documented as of July 15, 2026.
Strengths
- Network-level architecture sees AI use that browser-extension and web-proxy rivals miss: native desktop apps (Windows 11 Copilot, Office 365), IDEs and API-driven agent workflows, with no endpoint clients (Observe).
- An intent-based policy engine that goes beyond allow/block: warn, route and redact AI interactions by role, department and conversational intent (product).
- Real-time data tokenization lets employees use external AI while PII and credentials never leave the enterprise (data tokenization).
Limits
- Agent security (added January 2026) is monitoring and prompt-blocking: no agent containment, sandboxing, scoped-credential mechanism or kill switch is documented as of July 15, 2026.
- No buildtime posture assessment of agent configurations (unlike Zenity or Noma) — coverage starts at runtime traffic.
- No FinOps or token-cost management despite logging every AI interaction.
Questions buyers ask
Which AI security platforms can actually contain a compromised agent?
Strictly, containment means the agent executes inside an isolated runtime and cannot reach systems outside its allowed surface. In this set, Kosmoy's Action Capsule is the only true sandbox for arbitrary agents, MCP servers and models — kernel-enforced isolation with default-deny egress and a kill switch. Cisco ships a sandbox (open-source DefenseClaw) scoped to the OpenClaw runtime. Prisma AIRS enforces scoped agent identity and gateway policy but does not isolate execution; Zenity and Noma quarantine and block connections; WitnessAI monitors and shields. All are useful; only the first category makes unauthorized reach architecturally impossible.
Is Prisma AIRS or Cisco AI Defense better than Kosmoy for AI security?
For breadth of AI security, usually yes. Prisma AIRS and Cisco AI Defense offer model scanning, posture management and adaptive red teaming that Kosmoy does not, backed by large threat-research teams (Palo Alto Unit 42, Cisco Foundation AI) and existing enterprise agreements. Kosmoy wins a narrower requirement: kernel-enforced agent containment and a control plane that runs entirely in your own Kubernetes, air-gapped if needed. Security-led buyers wanting the widest surface shortlist the giants; regulated buyers who must enforce isolation and self-host shortlist Kosmoy — often alongside one of them.
How do the AI security acquisitions change the buying decision?
They concentrate capability and add integration risk. Prisma AIRS is Protect AI plus Koi plus Portkey stitched together, with the gateway in limited preview and the Portkey deal only closed in May 2026; Cisco AI Defense folds in Robust Intelligence and Astrix. The upside is one vendor and one contract; the risk is that recently acquired pieces are less mature than the marketing implies. Ask for the integration status and the deployment model in writing — several of these control planes are SaaS-only, which matters if sovereignty is a requirement.
Which platform is best for shadow AI and employee AI use?
WitnessAI, for the network-level employee-usage problem: it catalogs every AI app, agent and conversation without endpoint clients and enforces intent-based policies with real-time PII tokenization. Zenity and Noma are strong on shadow agents built on business platforms, and Kosmoy's master agent registry flags unregistered agents across Foundry, Bedrock, Vertex, Salesforce and ServiceNow as shadow AI. The right pick depends on whether your shadow-AI risk is employees using AI apps (WitnessAI) or ungoverned agents in your build platforms (Zenity, Noma, Kosmoy).
Can I run Kosmoy together with an AI security specialist?
Yes, and the combination is coherent rather than redundant: the security platform discovers AI, scores posture, scans models and red-teams them; Kosmoy registers agents with owners and risk tiers, routes their traffic through a policy gateway, and physically contains the ones that act autonomously. Several of these vendors position posture and runtime as layered controls — Kosmoy extends the stack one level further down, to enforced isolation and audit evidence. Detection plus containment is the pattern most regulated enterprises end up buying.
What does an AI security platform cost?
Almost every vendor here sells on enterprise quote — Zenity, Noma, WitnessAI, Cisco, Palo Alto and Kosmoy publish no price lists. Prisma AIRS uses credit-based subscription with token-consumption pricing for its runtime API, procurable via AWS Marketplace; the specialists often carry private marketplace offers too. Budget for the platform plus integration work, and if you are combining a detection specialist with a containment layer, price both — they solve different halves of the problem.
Methodology
Every factual claim on this page traces to vendor documentation, press releases or analyst coverage accessed on July 15, 2026 and cited inline or in the Sources list. Where a vendor does not document a capability, we say so with that date rather than treating absence of evidence as evidence of absence. Cisco's Astrix Security acquisition is reported at roughly $400M; Palo Alto did not disclose the Portkey price.
Radar scores follow the same rules on every Kosmoy comparison page: 10 is reserved for categorical architectural facts, specialists outscore Kosmoy on their own spoke — Prisma AIRS, Cisco, Zenity and Noma all rate higher than Kosmoy on security and red teaming — and containment is scored strictly, so sandboxed execution with scoped credentials and a kill switch scores high, scoped identity and connection blocking score mid, and monitoring scores near zero.
Disclosure: Kosmoy publishes this page. The mitigation is structural — Kosmoy wins one of four buyer picks, the detection and red-teaming segments go to the specialists outright, and the rubric concedes plainly that Kosmoy has no posture-management or red-teaming engine. See also the adjacent view from the governance side in our AI agent governance guide, and the research on shadow AI risk that motivates the discovery axis.
Sources
Every factual claim about another vendor on this page traces to that vendor's own published material or a named third-party source below.
- Palo Alto Networks secures agentic AI with Prisma AIRS 3.0 (Mar 23, 2026) — accessed July 15, 2026
- Palo Alto Networks completes acquisition of Portkey (May 29, 2026) — accessed July 15, 2026
- Palo Alto Networks completes acquisition of Protect AI (Jul 22, 2025) — accessed July 15, 2026
- Palo Alto Networks completes acquisition of Koi Security (Apr 14, 2026) — accessed July 15, 2026
- Cisco redefines security for the agentic era — AI Defense expansion (Feb 10, 2026) — accessed July 15, 2026
- Zenity inline prevention GA for Copilot Studio (Nov 18, 2025) — accessed July 15, 2026
- Noma launches Agentic Access Control (Jun 2, 2026) — accessed July 15, 2026
- WitnessAI $58M raise and agent security expansion (Jan 13, 2026) — accessed July 15, 2026
- Kosmoy Action Capsule — accessed July 15, 2026
- Kosmoy Platform — accessed July 15, 2026
- Kosmoy AI Gateway — accessed July 15, 2026
- Kosmoy AI Compliance — accessed July 15, 2026
- Cisco AI Defense product page — accessed July 15, 2026
- Cisco AI Defense data sheet — accessed July 15, 2026
- Cisco RSA 2026 agentic workforce announcement (Mar 2026) — accessed July 15, 2026
- DefenseClaw is Live (Cisco blog, Mar 27, 2026) — accessed July 15, 2026
- DefenseClaw GitHub repository — accessed July 15, 2026
- Prisma AIRS product page — accessed July 15, 2026
- AI Runtime Security API Intercept overview (deployment/SDK) — accessed July 15, 2026
- Prisma AIRS API on AWS Marketplace (SaaS/pricing) — accessed July 15, 2026
- Prisma AIRS runtime-security review (deployment, guardrail scope) — accessed July 15, 2026
- Zenity platform — AI Observability — accessed July 15, 2026
- Zenity platform — AI Security Posture Management — accessed July 15, 2026
- Zenity platform — AI Detection & Response (AIDR) — accessed July 15, 2026
- Zenity $38M Series B announcement — accessed July 15, 2026
- Guardian Agents / continuous contextual security (Business Wire, Mar 23, 2026) — accessed July 15, 2026
- Noma platform overview — accessed July 15, 2026
- Noma AI Runtime Protection — accessed July 15, 2026
- Noma AI Red Teaming — accessed July 15, 2026
- $100M Series B (PR Newswire, Jul 2025) — accessed July 15, 2026
- Kong Noma Runtime Protection plugin — accessed July 15, 2026
- WitnessAI product platform — accessed July 15, 2026
- WitnessAI Observe (shadow AI discovery) — accessed July 15, 2026
- $27.5M Series A (PR Newswire, May 2024) — accessed July 15, 2026
- WitnessAI EU AI Act compliance checklist — accessed July 15, 2026
Shortlisting for a regulated environment?
Kosmoy puts an inventory, a policy gateway and a containment sandbox around every AI your teams run — in your own Kubernetes.
Or email sales@kosmoy.com.