Control how your agents behave at runtime
Agents invoke tools, access data, and chain actions across sessions. The threat is rarely a single event. It's a series of individually reasonable actions that combine into something dangerous. Noma governs and monitors agent behavior at runtime, so agents can safely connect to sensitive systems and be productive.
How Noma AI agent runtime security works
Noma enables organizations to discover, govern, test, and protect AI and agents across the enterprise.
Define what agents are allowed to do
Set policies that govern which tools each agent can use, which actions are permitted, and which MCP servers it can connect to, scoped by user identity. Policies are enforced at the moment an agent acts, whether it's connecting to a new tool, invoking a function, or accessing data. Your teams work without friction. Agents that step outside their permitted scope get stopped before any damage is done.
Context-aware enforcement
Noma evaluates the complete chain of agent actions across a session: prompts, responses, tool calls, tool responses, skills used, interactions with other agents, and more. The Noma Runtime Context Engine also considers the identity behind the agent, the data it can reach, and baseline behavior over time. That combined context lets Noma enforce accurate policies on real risks, while reducing false positives.
Leverage the experience of the world's best security teams
Dozens of Fortune 500 security teams run Noma in production, and that experience ships in the product: hundreds of out-of-the-box policies, benchmarks, and protection profiles, tuned by industry, agent function, and agent type. Your agents start with protection already proven in similar environments.
Broad coverage across AI risks
Noma covers agents wherever they run: homegrown agents, SaaS agents, and endpoint agents. That includes agents talking to each other, where threats cross environment boundaries and tools scoped to one environment might miss an interaction. Across all agent types, Noma detects prompt injection, including indirect injection through tool responses, masks sensitive data inline, catches scope violations, and enforces guardrails you write in natural language. It's one platform, so you see and govern everything in one place instead of piecing it together across endpoint, cloud, and SaaS security tools.
Every AI surface, same enforcement
The same behavioral monitoring and policy enforcement applies whether the agent runs on Bedrock behind an AI gateway, on Copilot Studio through platform integrations, or on a developer's machine through native hooks inside Claude Code or Cursor. One set of policies, enforced consistently.
Security that adapts to your environment
Comprehensive coverage
Cover endpoint AI agents, SaaS agents, and homegrown AI from one platform, and ingest data across 80+ connectors to data platforms, EDR, model registries, version control, and more.
Open enforcement
Decouple governance from any single control point and enforce policy through AI gateways, MCP gateways, agent hooks, agent SDKs, and direct APIs, using the infrastructure already in the environment. Security should not force architecture decisions, it should adapt to them.
Multiple deployment options
Support for both on-prem and SaaS deployments ensuring your unique requirements are met so that no model, training data or security events leave your environment.
AI everywhere, secured by Noma
