AI workbench
SSH, Telnet, and SNMP collection keeps device facts beside AI analysis and its source evidence.
What is Network AI Ops
Network AI Ops is a local-first intelligent network operations workspace for network engineers, turning device management, topology discovery, AI inspection, endpoint tracing, and batch deployment into repeatable evidence-driven workflows.
Who it is for
- Network engineers managing devices, topology, inspections, and change evidence
- Operations teams requiring local deployment and auditable workflows
What problem it solves
Network troubleshooting often relies on personal experience and jumps across devices, topology, knowledge bases, and screenshots, making evidence hard to review.
Core capabilities
Topology management
LLDP/CDP neighbor data and NetBox Cable records are used to build and validate topology.
IP endpoint tracing
ARP, MAC, VLAN, interface, and device evidence is correlated to trace endpoint access paths.
AI inspection
Inspection tasks collect device state and combine it with the knowledge base to produce reviewable conclusions.
Batch deployment
Commands or configurations can be sent to multiple connected devices while preserving execution results for verification.
Typical workflows
- Maintain device and address data
- Collect configuration, interface, log, and neighbor evidence
- Run topology, endpoint tracing, or AI inspection tasks
- Review recommendations before batch changes
- Export reports and retain knowledge
Use cases
- Network diagnosis
- Device health inspection
- IP management
- Pre-change checks
Inputs
- Device inventory and connection details
- SSH, Telnet, and SNMP evidence
- NetBox or phpIPAM data
- Local operations documents
Outputs
- Layered network topology
- Endpoint access path
- Inspection reports and health recommendations
- Batch execution logs and audit records
Deployment and data boundary
- The desktop application runs locally and stores credentials and collected data in the user's environment
- AI capabilities require a user-configured model connection
- Production or organization-wide use requires prior licensing confirmation
System requirements
- Windows: 64-bit Windows; exact compatible versions are still being confirmed
- macOS: Apple Silicon M-series chips; Intel Macs are not supported; the minimum macOS version is still being confirmed
Current version and update
1.2.6
Published：2026-08-01
Content updated：2026-08-02
Downloads and verification
Windows x64
- Version
- 1.2.6
- Platform
- Windows
- Architecture
- x64
- Compatibility
- x64 for 64-bit Windows; exact compatible versions are still being confirmed
- Size
- 11.35 MB
- Published
- 2026-08-01
- SHA256
923ed8ba4b303d5dd72e57e9c513e0d465f8631619dd5a5104a0ca3fc2a708b4
macOS Apple Silicon
- Version
- 1.2.6
- Platform
- macOS
- Architecture
- Apple Silicon
- Compatibility
- Apple Silicon for M-series chips; Intel Macs are not supported; the minimum macOS version is still being confirmed
- Size
- 17.27 MB
- Published
- 2026-08-01
- SHA256
492320e77721b566643918b7c285d79172de0848a6a0f894236ac235e4bf58a0
Evaluation Edition and Extended Licensing
For personal learning, technical validation, small-scale testing, and non-production evaluation.
Existing data remains available in the Evaluation Edition; advanced capabilities follow the extended licensing scope.
Production or organization-wide use requires prior confirmation of the licensing scope.
Evaluation Edition Scope
- Devices: 20
- AI inspections / month: 10
- Endpoint traces / month: 5
- Linux servers: 3
- Batch devices / run: 3
- Audit retention: 7 days
Evaluation Edition Capabilities
- Device inventory, connection settings, and basic collection
- SSH terminal, SNMP collection, and core knowledge-base capabilities
- Basic link modeling and topology
- Local IPAM management and queries
- Local users, roles, recovery codes, and 7-day audit logs
Extended Licensing
- Telnet remote terminal and SNMP templates
- One-click device backup, inspection, and log analysis
- LLDP/CDP automatic link discovery and NetBox Cable synchronization
- Writing collected data to IPAM, data import/export, and migration backup
- Enterprise controller, child-client approval, license reporting, and sync policies
- OEM branding, installer name, icons, and copy customization
When extended licensing applies
- Enterprise production environments
- Larger-scale device management
- Higher-frequency inspection and endpoint tracing
- Longer audit retention
- Organization-wide use
- Custom deployment, adaptation, and technical support
- OEM or brand customization
Known limitations
- macOS supports Apple Silicon only; Intel Macs are not supported
- Minimum Windows and macOS versions are still being confirmed
- AI features depend on a user-configured model service
How it compares
Traditional NMS (SolarWinds, PRTG)
Traditional NMS focuses on monitoring and alerting. Network AI Ops focuses on diagnosis, automation, and evidence chain preservation.
AgenticOps
AgenticOps targets multi-system event correlation with a server-side multi-agent loop. Network AI Ops is a desktop app for day-to-day engineer troubleshooting and operations.
Ansible / automation scripts
Ansible specializes in configuration push and orchestration. Network AI Ops adds progressive diagnosis like topology, endpoint tracing, and AI inspection.
Frequently asked questions
Does Network AI Ops require a public cloud?
No. Core device, topology, collection, and audit workflows run locally; AI features use the model connection configured by the user.
Which installers are available?
Version 1.2.1 provides Windows x64 and macOS Apple Silicon installers. Intel Macs are not supported.
What does endpoint tracing produce?
It combines IP, MAC, VLAN, gateway, aggregation, and access evidence to identify the access path and final switch port.
Can the Evaluation Edition be used in production?
It is intended for learning, technical validation, small tests, and non-production evaluation. Production or organization-wide use requires licensing confirmation.
How is Network AI Ops different from AgenticOps?
Network AI Ops is a desktop app for daily troubleshooting, topology, AI inspection, and batch deployment. AgenticOps is a server-side open-source platform for multi-system event correlation with multi-agent diagnosis. They can be used independently or together.
Where is the data stored?
Device credentials, collected data, and audit logs stay in the desktop app's local environment. AI features use a model connection you configure — the provider does not automatically receive your device data.
Related technical guides
No complete English guide is published for this product yet.
Product access
Product screenshots
Video demos
AI Workbench
Natural-language tasks, knowledge selection, run traces, and diagnosis output in one workspace.
Topology Management
Layered topology, device placement, links, and SNMP status in one view.
IP Address Management
Manage VLANs, prefixes, IPs, scanning, and endpoint trace tasks.
Device Management
Maintain device inventory, connection profiles, collection history, and config versions.
Batch Deploy
Review target devices, scripts, uploads, execution logs, and audit results together.
Knowledge Base
Sync Markdown, PDF, Office, and CSV documents into the diagnosis flow.
Settings Center
Configure models, embeddings, SMTP/Webhook, backups, and enterprise controls.