Homegrown Agents
Noma discovers every agent across cloud platforms and code repositories, maps what each one can reach, tests them for vulnerabilities before production, governs what they're allowed to do, and monitors their behavior at runtime.
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
The Challenge
Your engineering teams build agents on AWS Bedrock, Azure AI Foundry, and Databricks, and in code with frameworks like LangChain and CrewAI. These agents carry the highest blast radius in your organization: customer-facing applications with access to sensitive data, chaining tool calls across production systems.
Secure SaaS agents
with Noma
Discovery
and posture
You can't secure agents you haven't found. Noma connects through APIs to your cloud providers, data platforms, model registries, version control, and notebooks, building a continuous inventory of every agent, model, MCP server, and skill.
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See each agent's
blast radius
The agent risk map correlates each agent's connections, permissions, data access, and connected agents. It surfaces toxic combinations, like untrusted input plus sensitive data plus a destructive action, and catches the common mistakes: secrets in agent instructions, excessive agency, unsandboxed agents.
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Stop risky behavior at runtime
A tested agent can still drift or be manipulated in production. Noma AI-DR evaluates each action in context: the event, the session before it, who the agent acts for, the data in reach, and behavior baselined over time. Detection covers prompt injection, data exfiltration, scope violations, and custom rules, with enforcement from alerting to real-time blocking.
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Red team every agent before production
Most automated testing tries one technique at a time, so defenses catch each one alone. Noma AI Red Team behaves like a real attacker, compounding techniques into multi-turn campaigns that escalate pressure at each turn. Pre-built scan profiles and compliance presets get campaigns running quickly.
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Part of the Noma platform
AI-SPM
Discover every AI agent, model, and MCP server across your enterprise.
Continuously assess posture and identify risk. Power access control and runtime detection.
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Access Control
Define what every agent is allowed to do. Enforce per-agent and per-tool policies for MCP connections, tool access, and actions. Stop unauthorized actions at runtime.
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AI-DR
Detect prompt injection, data exfiltration, and agent misuse. Analyze the full sequence of agent actions, not just prompts. Respond with context from discovery and access control.
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AI Red Teaming
Test AI applications for vulnerabilities before attackers do. Simulate multi-turn attacks directly in your CI/CD pipeline. Feed findings into AI-DR runtime policies.
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Built to Higher Standards.
FAQs
What are homegrown AI agents?
Homegrown agents are AI applications engineering teams built on cloud platforms like AWS Bedrock, Azure AI Foundry, and Databricks, or in code with frameworks like LangChain and CrewAI. They typically carry the highest blast radius in the organization.
How does Noma discover homegrown agents?
Noma connects through APIs to cloud providers, data platforms, model registries, version control, and notebooks, and builds a continuous inventory of every agent, model, MCP server, and skill.
Can Noma test homegrown agents before production?
Yes. Noma AI Red Teaming runs multi-turn adversarial campaigns against your agents and applications before release, and its findings feed directly into runtime detection policies.
How does Noma protect homegrown agents at runtime?
Noma AI-DR evaluates each agent action in context: the event, the full session, the identity behind the agent, the data in reach, and baseline behavior over time. Based on policy, it alerts, blocks, masks data, or routes to a human.
