What is NINA AI?
NINA AI is a multi-agent cybersecurity system built into Zynap. Unlike a standard AI assistant that answers questions or generates text, NINA AI takes action, directly inside your environment.
Ask about APT29 and it returns the full profile from our real-time threat intelligence database:
- TTPs
- IOCs
- associated malware
- confirmed victims
- C2 infrastructure
Tell it your workflow failed and it identifies the root cause, applies the fix, and re-executes to verify it works.
Describe the flow you need: subdomain reconnaissance, vulnerability analysis, Slack alerting, and it builds it directly in your canvas, node by node, with the right connections and configurations.
Six specialized agents operate behind every interaction, each with direct access to platform APIs and live data: threat intelligence, malware analysis, automated troubleshooting, workflow design, construction, and technical documentation.
NINA AI also ships with two capabilities that extend what your team can do with the platform.
What You Can Do on Nina
Local Agent Execution
Local Agent Execution lets you connect any tool, script, or AI model running on your own infrastructure directly into a Zynap security workflow.
The results flow back into the platform automatically, ready for downstream analysis, enrichment, or reporting.
This means you can run a local LLM against sensitive files, execute proprietary tooling that can’t leave your network, or spin up a custom scanner against internal targets, and treat the output as a standard node in your workflow.
Each organization gets fully isolated infrastructure – dedicated queues, storage, and scoped credentials. Your workloads run on your machine. Zynap handles the orchestration.
Agent Orchestration
Agent Orchestration lets you place an autonomous AI agent anywhere inside a Zynap workflow.
Rather than following a fixed sequence of steps, the agent receives a goal and a set of tools and reasons through how to complete the task: deciding which tools to call, in what order, and how to interpret the results. It can run up to 100 iterations, retaining full context throughout.
You configure each agent from scratch: the model, the instructions, the tools it can access, and the output format.
Agents connect to external tools via MCP (Model Context Protocol), which provides a standard interface for internal APIs, third-party services, and custom scripts. If a step fails or more context is needed, the agent adapts rather than stopping.
From the Team
NINA AI is live. Book a demo and we’ll walk you through what it looks like in your environment.
And if you want to understand how we got here, how we think about AI agents in security operations and what we learned building them, the Zynap Inside AI series is where that story starts.