Ask any network engineer about their worst outage and there’s a good chance it started with a change that looked safe. The problem isn’t carelessness — it’s that most teams have no way to see a change’s blast radius before they ship it.
From alerts to foresight
Traditional monitoring is retrospective: it tells you something broke, after it broke. Change intelligence is prospective. It answers a different question:
If I make this change, what will actually happen?
Phantom does this with two ingredients:
- A digital twin. A point-in-time snapshot of device configs, routes, and neighbors — captured before and after a change, tied to a change record.
- A self-hosted AI. A model reads the proposed change against current state and returns predicted impact, blast radius, risk, and a rollback — in plain English.
The workflow
Proposed change → model it against a “before” twin → predict the impact → approve → execute → compare against an “after” twin → flag any drift.
Before you ship, you get a prediction. After you ship, you get proof of exactly what changed — including anything unintended that nobody logged.
The part regulated teams care about
The AI runs on-prem, inside the same stack as everything else. Your configuration and topology are analyzed on-box and never sent to a third party. That’s why trading firms, carriers and utilities can finally put AI to work here, where cloud tools were a hard no.
Curious what Phantom would predict for your next change window? Book a demo.