The Tool Desk
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What NetBrain’s AI agents do
NetBrain calls its agent platform Agentic NetOps. Its agents are designed to use the network context and automation available in the NetBrain platform to perform specific operations work—not simply answer questions from generic network knowledge.
The rollout began with NetBrain’s February 10, 2026 announcement of agentic AI in core workflows for investigating complex network issues, diagnosing them, suggesting fixes, and supporting engineers during remediation. On September 22, 2026, NetBrain announced a broader team of governed agents: the existing Diagnosis Agent joined by Change and Assessment agents. NetBrain says these capabilities cover diagnosis, change, assessment, and prevention, with engineers retaining approval control.
The three announced agent roles
| Agent | Primary job |
|---|---|
| Diagnosis Agent | Investigates an incident, runs relevant diagnostics, and produces a structured root-cause analysis for engineer review. |
| Change Agent | Evaluates a proposed change, works with engineers to make it, and checks the outcome afterward. |
| Assessment Agent | Scans for known issues and deviations from a baseline so teams can address them proactively. |
How the Diagnosis Agent investigates an incident
An investigation can start when an engineer launches it or when a connected ITSM ticket, alert, or webhook triggers it. The precise checks depend on the tools, data, and diagnostic intents available in a customer’s environment.
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- Gather the incident context. The agent reads the available tools and the incident details associated with the ticket, alert, or manual request.
- Consult connected systems. It can query connected monitoring systems and use cross-domain information made available through integrations.
- Run diagnostic intents. It selects and runs relevant diagnostic procedures, then navigates the customer’s network topology to investigate the affected devices and paths.
- Present findings. It synthesizes the results into a structured root-cause analysis for an engineer to review.
This is an investigation workflow, not a guarantee that every incident will have a single, certain root cause. The result depends on the live context, connected systems, and relevant tools available to the agent; the engineer remains responsible for assessing the findings.
What network data and context the agents use
NetBrain says its agents reason over a Context-Aware Digital Twin and live network context. The model brings together device, topology, path, and intent data. The vendor states that its context model covers more than 150 hardware vendors; that is a NetBrain-reported coverage figure, not an independently audited measurement.
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NetBrain’s Agent Skills encode site-specific knowledge and best practices so customers can apply local operating knowledge without retraining a model. The company also describes AI Path Doctor, which validates network paths, flags inaccuracies, and can generate remediation runbooks.
Cross-domain integrations can add application and infrastructure information from ITSM, security, and application-performance-monitoring systems. NetBrain cites Dynatrace as an example of context that can help teams distinguish a network problem from an application-side issue. How useful that distinction is in practice depends on the quality and availability of the connected data.
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Do the agents make network changes automatically?
NetBrain describes the agents as read-by-default and scoped by role. Its product description ranges from supervised investigations to automatically triggered diagnosis, but that does not mean every action is autonomous: automatic initiation of diagnosis is different from permission to change a network.
For network changes, NetBrain says the agent requires human review or pre-approved automation. The Change Agent can evaluate a proposed change, work with an engineer to make it, and confirm the result afterward. Role-defined scope, approval controls, and a full audit trail are intended to constrain and document the work. Teams evaluating the platform should confirm which actions are enabled, who can approve them, and how pre-approvals and audit records are configured in their own deployment.
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Integrations and working with other agents
NetBrain says its platform exposes open API and MCP-native connections. It lists ServiceNow, Dynatrace, Splunk, and Cisco Cloud Control among the systems that can work with its live context and guardrails. It also says external agents built on Claude or Codex can connect. These are vendor-listed integration examples; availability and supported functions may vary by release, configuration, and contract.
For an operations team, the practical question is not just whether a connector exists. Check whether the integration supplies the specific ticket, alert, application, security, or network data needed for the workflow, and whether the connected agent can only read that information or is also authorized to initiate automation.
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What NetBrain’s published results do—and do not—show
NetBrain reports several outcomes for the platform and its customers. These are company statements, not independently validated benchmarks in the cited announcements:
- Under five minutes: NetBrain says a leading health insurer used Deep Diagnosis to resolve a VPN connectivity issue that had persisted for weeks in under five minutes. This is a vendor-reported customer example, not a general resolution-time guarantee.
- 40% or more of tickets: NetBrain says cross-domain context can eliminate this share of tickets. The figure is a company claim, not an independently confirmed ticket-reduction result.
- 85% less change-execution and validation effort: In the September 22, 2026 announcement, CEO Bernadette Nixon said customers already use the platform to reduce this effort by 85%. The announcement does not establish this as an independently validated or universal result.
- Agentic AI adoption forecast: NetBrain’s May 10, 2026 market-guide citation attributes to Gartner a forecast that agentic AI would move from less than 1% in early 2026 to the most common approach by 2030. This is a Gartner forecast as reproduced by NetBrain, not a measured adoption result.
These figures describe different things—one customer example, a claimed ticket reduction, a claimed effort reduction, and a forecast—so they should not be treated as interchangeable evidence of diagnostic accuracy or performance.
How to evaluate the platform for your network
Before relying on an agent in operational workflows, assess whether it has the context, access, and controls your team needs. Useful evaluation questions include:
- Context fidelity: Does it have current device, topology, path, and intent information for the parts of the network in scope?
- Diagnostic traceability: Can engineers see which tests and data underpin the root-cause analysis?
- Action governance: Are role boundaries, human approvals, pre-approved actions, and audit trails clear and appropriate?
- Coverage: Do supported devices and hybrid-cloud environments match your estate? Treat the 150+ vendor figure as NetBrain’s stated coverage, then verify the specific devices and use cases you operate.
- Integration fit: Do the required ITSM, monitoring, security, and APM connections provide the data and functions your workflows need?
- Extensibility: Can Agent Skills, runbooks, APIs, or MCP connections accommodate your local procedures without granting excessive access?
- Evidence quality: Separate vendor-reported examples and claims from results demonstrated in your own controlled evaluation.
A practical pilot can compare the agent’s findings with engineer-led diagnosis on representative incidents, inspect the evidence behind its conclusions, and test approval boundaries before enabling any pre-approved changes.
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