Platform · Change Intelligence
Phantom captures a digital twin of your network, then a self-hosted AI predicts what a proposed change will do — before it ships. Afterward, it proves exactly what changed. All on-prem; no config ever leaves your network.
Capture a pre-change and post-change snapshot of device configs, routes and neighbors, tied to a change record.
A self-hosted LLM reads the change and current state and returns predicted impact, blast radius, risk, and a rollback — in plain English.
Diff the twins after execution to catch unintended changes nobody logged.
Remove a node or link from the model and see the blast radius before an outage — not during one.
An MCP server exposes the platform so Claude or GPT can query devices, inspect topology and analyze changes directly.
On-prem AI
A fine-tuned model is self-hosted in the stack, with pluggable providers if you choose. Sensitive configuration is analyzed on-box and never sent to a third party — the reason regulated teams can finally use AI here.