Imaging AI should clear the backlog,
not get in the way.
Demand for imaging keeps climbing, and every new model is supposed to help your radiologists read faster and with more confidence. Ferrum makes sure each one earns its place — deploying inside the worklist they already use, proven on your patients before go-live, and monitored so it keeps helping long after.
Every new tool adds another login and another blind spot.
One more app outside PACS, so it adds clicks instead of clearing the worklist.
Vendor accuracy comes from someone else’s scanners and patient mix.
Nothing watches the model, so you learn it stopped helping from a missed finding.
Deploy, manage, and measure every model.
Route every model into PACS and the native viewer.
See what is approved, live, and ready to scale across sites.
Validate on your patients, then track turnaround and capture.
An open platform your team owns, governs, and scales.
Ferrum’s AI Governance Suite consolidates the spend, surfaces the cost, and proves the return.
If a model lives in another app or adds clicks, radiologists route around it, and the backlog it was meant to clear never moves.
A model proven on another system’s scanners and patients can read differently on yours, and your radiologists feel it first.
Without monitoring you have no read on whether a tool still earns its place, and no turnaround or capture numbers for the people funding it.
Build the infrastructure once. Every future model reuses it. Security, contracts, and integrations are solved permanently — not per vendor.
One open ecosystem, governed consistently across every model type. You set the strategy. Ferrum enforces it — regardless of where a model came from.
Every model, every metric, one source of truth. Answer portfolio risk, clinical performance, and ROI questions on the spot — not after a two-week data pull.