NetPilot

AI for Network Engineers

The AI agent that builds and runs the lab — and the real CLIs are always one SSH away.

Describe a network in plain English and the agent designs, deploys, and validates a multi-vendor lab on real network OS images.

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AI for Network Engineers: 5 Real Tasks on a Real Cisco Lab, Scored · Watch on YouTube

See It in Action

The video above gives the agent five real jobs on a Cisco IOS lab: design, configure, deploy, find a planted OSPF fault from a user's symptom, and write the handover. Every verdict is checked on the CLI. Read the run and the scorecard in five tasks, one scorecard, or repeat the test with the three prompts we used.

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What AI looks like when it's built for network engineers

An agent that does the build-and-validate work end-to-end — with the real CLI always one SSH away. Four things that set an agentic lab apart from a chat box.

An agent, not a chat box

Describe the network — the agent designs the topology, writes per-vendor configs, deploys, and validates. It does the work, not just the talking.

The alternative

General LLMs write config text you still have to wire up, deploy, and verify yourself, device by device.

The CLI is always one SSH away

Dual-path by design: agent for speed, classic CLI for control. SSH into any device, run real vendor NOS, verify or work the traditional way.

The alternative

Agent-only tools hide the network behind a UI; you lose the real CLI engineers actually trust.

Multi-vendor in one lab

17+ NOSes in a single topology. Ask for eBGP between a Cisco edge and a Juniper transit router and it writes both syntaxes at once.

The alternative

Vendor copilots (Cisco AI Assistant, Juniper Marvis) are single-vendor and tied to production gear.

Lab in ~2 minutes

Prompt to working multi-vendor lab on real NOS images in ~2 minutes — then iterate conversationally across every device.

The alternative

DIY EVE-NG/GNS3: VMs, image hunting, and hours-to-days of per-device manual setup before the first test runs.

What AI does in a network engineer's day

Three everyday workflows where an agent removes the toil — and you still drive the CLI for the parts that matter.

Design & build a lab from a prompt

Describe the topology in plain English — the agent designs it, generates per-vendor configs, and deploys a multi-vendor lab on real NOS images in ~2 minutes. No drag-and-drop GUI and no VM provisioning; built-in NOSes run instantly, commercial vendors via bring-your-own-image (BYOI).

Build a lab →

Validate a change before prod

Mirror the affected segment, capture a pre-change snapshot, apply the candidate BGP/ACL/OSPF change, then diff post-change state — on real CLIs, before it touches production.

Validate a change →

Troubleshoot & reproduce on real CLIs

Rebuild a customer or production issue on real multi-vendor NOS code, SSH into any device, and work it the classic way — the agent sets the stage, you drive the CLI.

Reproduce an issue →

Engineer tasks you can hand to the agent

From OSPF and BGP to EVPN fabrics and firewall policy — describe it, the agent builds it on real multi-vendor NOS code, and you verify on the CLI.

Prompt-to-lab from plain English

Describe the network in plain English — the agent designs the topology, generates per-vendor configs, and deploys a runnable multi-vendor lab on real NOS images in ~2 minutes.

Per-vendor config generation

One intent, correct syntax everywhere — the agent writes Cisco IOS, Junos, and Arista EOS at once, so multi-vendor interop is a prompt instead of a week of syntax lookups.

Stage a change before prod

Rehearse a BGP, ACL, or OSPF change on an isolated mirror lab — capture pre-change state, apply, and diff post-change on real CLIs before it ever touches production.

Reproduce & troubleshoot an outage

Rebuild a customer or production issue on real multi-vendor NOS code, then SSH into any device to chase the root cause — the agent sets the stage, you drive the CLI.

Multi-vendor routing fabrics

eBGP/iBGP, multi-area OSPF, IS-IS, and EVPN/VXLAN across multiple network OSes in one topology — Nokia SR Linux built in, Cisco/Juniper/Arista via BYOI — verify cross-vendor behavior on live neighbor and routing state.

Agent-run first-pass validation

The agent runs the show commands — routing tables, neighbor state, reachability — and reports evidence, so you review the result instead of typing every command yourself.

Test automation against the lab

Point Ansible, Netmiko/Nornir/NAPALM, or Terraform at the lab's real NOS CLIs to prove a playbook or pipeline, then take what you've validated back to production.

Firewall & service policy interop

Wire Palo Alto or Fortinet zones and NAT between Cisco segments, layer in DHCP/DNS/NTP/QoS and IPSec/DMVPN, and confirm policy behavior end-to-end (commercial vendors via BYOI).

Build labs from the assistant you already use

NetPilot is in the ChatGPT plugin directory and the Claude connector directory. Ask your assistant for a network lab and it builds it on real network operating systems. Any AI assistant that connects to MCP servers works too.

One prompt in Claude built Arista, Nokia and FRR routers in three autonomous systems, brought every eBGP session up and pinged loopback to loopback across all three. One prompt in ChatGPT built a Cisco, an Arista and a Junos router in OSPF area 0, and every neighbor came up FULL on each router's own CLI. There is no MCP server to build and nothing to install.

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See the multi-vendor run in Claude·See the multi-vendor run in ChatGPT·Connect your assistant

For teams

NetPilot connects to the network systems you already run, over API or MCP. Our team builds each integration for your workflow. NetBox, Nautobot and Nornir are a few examples. Anything with an API or an MCP server works. Your own AI agents can also connect to NetPilot over MCP and build labs on it.

NetPilot for teams·See how the integrations work·Compare 7 tools for your own AI agent

The AI-for-network-engineers landscape, honestly

Different AI tools own different lanes. NetPilot's is the lab — build, run, and validate; the others own production ops, live-network automation, and broad Q&A.

Primary lane
NetPilot
Build + run + validate in a lab
General LLMs (ChatGPT / Claude)
Broad Q&A + writing config text
Vendor copilots (Cisco AI / Marvis)
Operate production gear (single vendor)
AIOps (Selector / Itential / Forward AI)
Monitor + automate the live network
Builds a runnable lab
NetPilot
Multi-vendor lab in ~2 min
General LLMs (ChatGPT / Claude)
Text only — you wire it up
Vendor copilots (Cisco AI / Marvis)
Production ops, not a lab
AIOps (Selector / Itential / Forward AI)
Models / automates prod
Runs real NOS code
NetPilot
Real NOS images, SSH access
General LLMs (ChatGPT / Claude)
No runtime
Vendor copilots (Cisco AI / Marvis)
On live production devices
AIOps (Selector / Itential / Forward AI)
Acts on live devices
Multi-vendor in one place
NetPilot
17+ NOSes in one topology
General LLMs (ChatGPT / Claude)
Knows every vendor's syntax
Vendor copilots (Cisco AI / Marvis)
Single vendor
AIOps (Selector / Itential / Forward AI)
Vendor-agnostic
Closes the loop (deploy + validate)
NetPilot
Designs → deploys → validates
General LLMs (ChatGPT / Claude)
You execute + verify
Vendor copilots (Cisco AI / Marvis)
Within the vendor's stack
AIOps (Selector / Itential / Forward AI)
For live-network workflows
Touches production
NetPilot
No, isolated lab
General LLMs (ChatGPT / Claude)
Never (advice only)
Vendor copilots (Cisco AI / Marvis)
Yes — that's its job
AIOps (Selector / Itential / Forward AI)
Yes — that's its job
Safe place to rehearse a change
NetPilot
Stage + diff before prod
General LLMs (ChatGPT / Claude)
Suggests, can't prove
Vendor copilots (Cisco AI / Marvis)
Acts on prod
AIOps (Selector / Itential / Forward AI)
Change windows on prod

Want the full tool-by-tool ranking? Best AI Tools for Network Engineers in 2026 ranks twelve tools into tiers — labs, vendor copilots, digital twins, and automation-code assistants.

Which AI should a network engineer reach for?

Pick other AI tools when you need:

  • •General LLMs (ChatGPT, Claude) for broad Q&A and drafting config snippets
  • •Vendor copilots (Cisco AI Assistant, Juniper Marvis) for operating production gear — single-vendor
  • •AIOps (Selector AI, Itential FlowAI, Forward AI) for monitoring and automating the live network
  • •A formal verifier when you need offline config proofs without running the network

Pick NetPilot when you need:

  • •Build a multi-vendor lab from plain English in ~2 minutes
  • •Run real NOS code and SSH into any device to verify
  • •Stage and validate a BGP/ACL/OSPF change before it touches prod
  • •Reproduce a production issue on real multi-vendor CLIs to troubleshoot it

Verdict:Vendor copilots own production operations and LLMs own broad Q&A — reach for those when that's the job. NetPilot is the agentic lab: build, run, and validate on real multi-vendor CLIs — with the classic CLI always one SSH away. Most engineers use more than one; these are complementary, not either/or.

AI for Network Engineers — FAQ

What AI actually does for a network engineer, where it fits, and where the CLI stays.

Yes. The most useful AI for network engineers today is an agent that does real work, not just a chat box: NetPilot takes a plain-English description ("two Cisco edge routers running eBGP, an Arista leaf-spine fabric, a Juniper transit AS") and designs the topology, writes correct per-vendor configs, deploys a multi-vendor lab on real network OS images in ~2 minutes, and validates it on live CLIs. Alongside that, general LLMs (ChatGPT, Claude) are strong for broad Q&A and writing config snippets, vendor copilots (Cisco AI Assistant, Juniper Marvis) help operate production gear, and AIOps platforms (Selector AI, Itential, Forward AI) monitor and automate the live network. NetPilot owns the build-and-validate-in-a-lab lane.
Yes, this is what an agentic tool like NetPilot does. Describe the topology in plain English or paste sanitized configs, and the agent designs it, generates containerlab YAML and per-vendor device configs, deploys to cloud-hosted real NOS images in ~2 minutes, and gives you SSH into every device. A single lab can mix multiple network OSes. Nokia SR Linux, FRR, and Linux endpoints are built in, while commercial images (Cisco IOL, Juniper cRPD, Juniper vJunos (router and switch), Arista cEOS, Palo Alto, Fortinet, Aruba AOS-CX, Dell SmartFabric OS10, MikroTik RouterOS (CHR)) run via bring-your-own-image (BYOI). MikroTik RouterOS (CHR) and SONiC (community VS) are preloaded on every lab VM, replaceable with your own versions. You then iterate conversationally ("add an OSPF area, move that peer to a route reflector") and the agent updates configs across all devices.
Concretely: build a multi-vendor lab from a prompt instead of hand-wiring it; translate one intent into correct Cisco, Juniper, and Arista syntax simultaneously; stage and validate a BGP/ACL/OSPF change before it touches production; reproduce a customer or production issue on real NOS code to troubleshoot it; and run first-pass validation (routing tables, neighbor state, reachability) so you review evidence instead of typing every show command. NetPilot does all of this as an agent, and you keep full CLI access via SSH for the parts you want to drive by hand.
No — AI changes the job, it doesn't delete it. AI agents now do the toil (build the lab, write per-vendor configs, deploy, run first-pass validation), and engineers move up to design intent, judgment, and owning the change. The agent proposes; the engineer decides, verifies on the real CLI, and signs off. We cover this in depth in our guide, Will AI Replace Network Engineers? An Honest Answer for 2026.
An AI assistant answers questions and writes config text — you still wire it up, deploy it, and verify it yourself (ChatGPT and Claude work this way). An agentic AI plans, acts, observes, and iterates: it designs the topology, generates the configs, deploys the lab, runs validation on live CLIs, and fixes what's broken — closing the loop instead of handing you a wall of text. NetPilot is agentic. For a deeper breakdown, see Agentic AI for Network Engineers: What It Means and Why It Matters.
No — the CLI is always there, and that's deliberate. NetPilot is dual-path: the agent for speed (design, generate, deploy, validate from plain English) and the classic CLI for control. SSH into any device, run the real vendor NOS, and verify or work the traditional way whenever you want. Agent-only would lose engineer trust; CLI-only would undersell the agent. Both paths are always available.
17+ network OSes and growing. Nokia SR Linux, FRR, and Linux endpoints are built in. Commercial vendors (Cisco IOL, Cisco IOS XR (XRd), Cisco NX-OS (Nexus 9300v), Juniper cRPD, Juniper vJunos (router and switch), Arista cEOS, Palo Alto PAN-OS, Fortinet FortiGate, Aruba AOS-CX, Dell SmartFabric OS10, MikroTik RouterOS (CHR)) run via bring-your-own-image (BYOI). MikroTik RouterOS (CHR) and SONiC (community VS) are preloaded on every lab VM, replaceable with your own versions. Custom NOS images (e.g. Cisco IOS-XE, Juniper vMX) are built for you. The agent handles vendor-syntax differences automatically: ask for "eBGP between the Cisco edge and the Juniper transit router" and it writes correct Cisco and Juniper CLI at the same time, so multi-vendor interop is a prompt, not a week of syntax lookups.
MCP (Model Context Protocol) is the standard way AI agents talk to tools. For network engineers it means your AI agent can use your network tools directly: read NetBox, query a model of the network, or build a lab. NetPilot is in the ChatGPT plugin directory and the Claude connector directory, and any AI assistant that connects to MCP servers builds and validates multi-vendor labs on it. For teams, NetPilot's agent also connects to your stack to build labs from your real configs. NetBox, Nautobot and Nornir are a few examples, anything with an API or an MCP server works, and our team builds each integration for your workflow.
You decide. By default NetPilot builds an isolated lab on cloud-hosted containerlab, separate from your production devices. You stage changes, reproduce issues, and run automation (Ansible, Netmiko/Nornir/NAPALM, Terraform) against the lab's real NOS CLIs, then carry what you've proven into your own cutover. Access to live devices is opt-in: read-only show commands through an integration, or a custom agent that NetPilot builds and delivers, which acts through the approval steps your team sets. For compliance or air-gapped teams, a self-hosted / on-prem deployment option is available.

From the blog

Best AI Tools for Network Engineers in 2026

Twelve AI tools ranked into tiers — labs, vendor copilots, digital twins, and automation-code assistants. The deep head-to-head.

Will AI Replace Network Engineers?

An honest answer for 2026 — what AI genuinely automates, what it structurally can't, and how to stay valuable.

Agentic AI for Network Engineers

What agentic actually means — plan, act, observe, iterate — and where it fits in the network toolchain.

Can AI Build a Network Lab?

Yes — here's how AI designs topologies, generates vendor configs, and deploys working labs from plain English.

Explore NetPilot

AI Network Emulator

The category page — the AI-native multi-vendor network emulator behind everything on this page.

Online Network Lab

Spin up a multi-vendor lab in your browser from a plain-English prompt — no install.

Network Change Validation

Stage BGP, ACL, and routing changes on an AI-built mirror lab before they reach production.

Put the AI to work

Describe a network in plain English. The agent builds the lab on real NOS images in ~2 minutes — then SSH in and drive the CLI yourself.

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