ZenAI · On-premises AI
ZenAI is not a chatbot bolted onto a dashboard. It reasons over the structured telemetry already inside ZenPlus — devices, flows, traces, maps, alerts, and reports — to summarize incidents, explain probable cause, and recommend safe next actions, with your operators in command.
Built for your data boundary
ZenAI is designed to run inside your environment and work from facts, not screenshots. It reads the structured telemetry Zentryc already collects, proposes explicit actions you can audit, and keeps a human in command of every decision.
What ZenAI does
Six grounded capabilities built around how NOC and security teams actually investigate, decide, and report — all inside your environment.
Turn alert lifecycle, recent outages, and report data into a clear, shareable incident narrative for operators and leadership.
Correlate availability, device latency, interface utilization, traffic spikes, and alerts to explain why a site or service is degraded.
Suggest safe, auditable steps — run diagnostics, check traps, verify config backup, or open a channel route — with the operator in command.
Ask questions across devices, flows, traces, maps, and alerts and get grounded answers from structured telemetry instead of screenshots.
ZenAI is built to reason over operational data inside your environment, aligned with the same on-premises model as the rest of Zentryc.
Role-aware workflows and explicit actions keep AI assistance useful and accountable without handing over control of the NOC.
AI for NOC operations
AI for NOC operations uses structured monitoring and observability data to help operators reduce alert noise, summarize incidents, correlate probable causes, scope impact, query telemetry, and choose the next diagnostic or response step.
An availability change, alert, traffic spike, service error, trace anomaly, or configuration event supplies the incident starting point.
Bring together devices, interfaces, flows, services, traces, maps, alerts, configuration state, and recent operational history for the affected scope.
Relate changes across time, assets, sites, links, applications, and alerts so operators can investigate a reasoned path instead of isolated dashboards.
Identify which sites, services, devices, interfaces, applications, or users are implicated and which parts of the environment remain healthy.
Name the next safe steps—run diagnostics, inspect traps, verify a configuration backup, review a trace, or route an incident update—without hiding the reasoning.
Preserve the summary, evidence, proposed actions, operator decisions, and incident update so the workflow can be reviewed and improved.
AIOps and agentic operations
AIOps commonly focuses on detecting anomalies, grouping alerts, correlating events, and predicting operational risk. Agentic NOC workflows add a structured path from that insight to a named task: gather evidence, scope impact, draft an update, recommend a diagnostic, or prepare a response step.
ZenAI is designed around this second layer while preserving operator control. The useful unit is not a vague AI answer; it is a grounded explanation with the evidence used, the impact found, and the next action being proposed.
Operational guardrail
ZenAI can summarize, correlate, query, and recommend, but a recommendation is not the same as permission to execute. Role-aware workflows keep operators responsible for consequential actions and make the proposed step visible before it runs.
Example agentic workflows
ZenAI is grounded in real investigation paths. It works the way an operator does — correlate signals, scope impact, draft the update, and propose the next safe step — while you stay in control of what actually happens.
Correlate availability, device latency, interface utilization, and active alerts to surface probable cause for an affected site or service.
Scope the impact of a traffic spike using top talkers, protocols, and the interfaces affected, so the team knows where to look first.
Draft a clear, shareable update from alert lifecycle, recent outages, and report data for both operators and leadership.
Suggest auditable steps — run diagnostics, check traps, verify config backup, or open a channel route — with the operator deciding what runs.
Guardrails
ZenAI is designed to make the NOC faster without removing operator judgment or moving your data outside your environment.
ZenAI is built to reason over operational data inside your environment, aligned with the same on-premises model as ZenPlus and ZenShield.
Actions are named and recorded — acknowledge, run diagnostics, back up config, open a channel route — so AI suggestions remain traceable.
Role-aware workflows keep humans deciding what executes. ZenAI assists with triage, summaries, and next steps — it does not replace the NOC.
Common questions
It is the use of structured monitoring and observability data to help operators reduce alert noise, summarize incidents, correlate probable causes, scope impact, query telemetry, and choose the next diagnostic or response step.
ZenAI reasons over structured Zentryc context including devices, availability, interfaces, NetFlow, services, traces, maps, alerts, configuration state, and reports.
No. ZenAI assists with summaries, correlation, explanations, and named recommendations. Role-aware workflows keep a human responsible for deciding what executes.
Yes. ZenAI is designed to run inside the customer environment without requiring telemetry, credentials, reports, or AI context to become a vendor-cloud dependency.
Get started
See how ZenAI reasons over live Zentryc telemetry to summarize incidents, explain probable cause, and recommend safe next actions — entirely on-premises.