Govern and Secure AI Agents Everywhere They Run
AI adoption is outpacing security across every enterprise. Noma lets you take back controcl without slowing down.
Acme Inc.
Industry Co
Robust AI Security
Security and Governance
AI and Agents
Industry Co
RealBusiness
Acme Inc.
Industry Co
Robust AI Security
Security and Governance
AI and Agents
Industry Co
RealBusiness
Three AI environments. One security gap.
AI agents run in three distinct environments across your organization, each with different architecture, different builders, and different risks.
01
RUN BY EMPLOYEES
Endpoint agents
Employees run Claude Code, Cursor, Codex, and personal AI agents on their machines, connecting them to dozens of MCP servers that reach into production code, internal APIs, and sensitive data. There's no approval process and very little visibility into what these agents are doing.
Noma for Endpoint Agents
02
BUILT BY ENGINEERING
Homegrown AI
Engineering teams build AI applications on AWS Bedrock, Azure AI Foundry, Databricks, and in code with frameworks like LangChain and CrewAI. These carry the highest blast radius: customer-facing apps with access to sensitive data, agents chaining tool calls across production systems.
Noma for Endpoint Agents
03
BUILT BY BUSINESS TEAMS
SaaS agent platforms
Business analysts, sales ops, HR, and finance teams build agents on Microsoft Copilot Studio, Salesforce Agentforce, and ServiceNow, often without telling security. Enterprises routinely discover 10 to 100x more agents than expected on these platforms.
Noma for Endpoint Agents
Why Noma
Every AI surface, no blind spots
Noma covers all agent environments: endpoint, homegrown, and SaaS. You get discovery, posture management, access control, red teaming, and AI-DR across every one of them.
Full behavioral context for detection
One agent action looks fine on its own. The risk is in the sequence: read customer records at step one, email them out at step four. Noma has full context into agent behavior, across a session and over time.
One place to manage AI security
Discovery, access control, adversarial testing, and runtime detection feed each other. What discovery finds shapes your access policies. What red teaming breaks becomes an enforced rule in production. You define your AI constitution in one place.
Open enforcement
Other tools make you re-architect: route all traffic through their gateway, deploy sensors org-wide. Noma enforces policy through what you already run. Agent hooks, multiple gateways, EDR and MDM, Agent SDKs, or direct APIs.
Four ProductsÂ
That Share Intelligence
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Use cases
Agentic identity
Know who your agents are acting as, what they're allowed to do, and whether their actions match the user's intent.
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Agentic behavioral guardrails
Access control defines the boundaries. Behavioral detection enforces them. Both share context so enforcement is precise.
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MCP security
Discover, assess, and govern every MCP server in your organization. Detect tool poisoning and supply chain attacks.
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Compliance and Reporting
Answer the board's AI risk question with evidence: inventory, framework mappings, test results, and audit trails.
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AI Asset Discovery
Find every AI agent running in your organization, including the ones nobody ever told security about. New agents are flagged the moment they appear.
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AI Supply Chain Security
Scan and govern your entire AI supply chain: models, MCP servers, tools, and packages you rely on. Every component gets a clear risk status.
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Coding and AI Assistant Security
Secure every coding assistant and AI developer tool. Discover usage, protect sensitive data, enforce policy at every step.
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AI Agent Control Plane
A single governance layer that spans discovery, access control, and runtime enforcement across every AI surface.
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