Tag an IV pump, a bed or a wheelchair and see where it is — read by the iPhones your staff already carry. No access points to mount. No gateways to wire. No year-long install project.
Clinical staff lose time every shift looking for pumps, chairs and carts that are somewhere in the building — just not where they are supposed to be.
When nobody can find the fleet, the answer is to rent more of it, or buy more of it. Utilisation stays invisible either way.
A missing pump delays a procedure. A missing chair delays a discharge. The cost lands in throughput, not in the equipment budget.
The usual fix is a full real-time location system: sensors in the ceilings, gateways in the closets, a capital project, and a multi-year contract. That is why most hospitals tag a single department and stop.
NavvTrack is already deployed on thousands of hospital iPhones. Those devices move through every corridor, every shift. That is a reader network you have already paid for — it just was not reading anything yet.
Stick or strap a NavvTrack Tag to the equipment. It is sealed, wipeable, and has no wires, no charger and no setup.
Every NavvTrack-managed iPhone that walks past picks up the tag and reports it, with the floor and zone it was seen in.
The tag appears on the same indoor floor map your teams already use to find devices and each other.
Because coverage follows your staff, the busiest areas of the hospital get the densest coverage automatically — and a ward with no NavvTrack phones in it is the one place this approach will not see. We will tell you that honestly during design.
Infrastructure-based systems from vendors such as CenTrak and Kontakt.io buy you certainty — room-level accuracy, everywhere, continuously. Both now also sell lighter Bluetooth modes that ride your existing wireless access points. We are not going to pretend those need rewiring, because they do not.
The real difference is what does the listening. Every RTLS on the market reads tags with fixed readers — ceiling devices, gateways, or BLE-capable access points placed on a density grid. We read them with the managed iPhones your staff already carry through every room on every shift. No vendor in healthcare RTLS currently does that.
| Infrastructure-based RTLS | NavvTrack | |
|---|---|---|
| What reads the tags | Fixed readers — ceiling devices, gateways, or BLE-capable access points | The managed iPhones you already deploy |
| Density requirement | A reader grid — published guidance runs to roughly one gateway per 800–1,000 sq ft for zone level, tighter for sub-room | None — coverage follows staff movement |
| Dependency on your network | Often a BLE-capable AP estate, so an access-point refresh can become a prerequisite | None beyond the phones already enrolled |
| Accuracy model | Room-level, continuous, guaranteed inside the installed footprint | Zone and floor level, refreshed as staff pass |
| Low-traffic areas | Consistent — readers are always there | Sparser — depends on people walking through |
| Commercial model | Per bed per use case, typically on a 3–5 year term | Per device per month, alongside the fleet you already license |
| Tracks your iOS fleet and teams too | Separate product, if offered | Same platform, same map |
Where we are the wrong answer: infant protection, patient elopement, and regulated temperature monitoring all need guaranteed continuous coverage. Buy an infrastructure system for those. We will tell you so on the first call.
Rather than quote a brochure number, here is the reported accuracy from a live health-system deployment over the last 30 days — 314,000 indoor position fixes across a working iPhone fleet, on floors we have surveyed for indoor positioning.
Median reported horizontal accuracy indoors
of indoor fixes reported within 5 m (99% within 10 m)
of indoor fixes carry a floor level, not just a point
The measured numbers are the accuracy estimates each iPhone reports with its own position (a 68% confidence radius), not survey-measured error against known points. 90th percentile was 4.2 m; upper floors with less foot traffic reported ~5 m rather than 2 m. Floor-level positioning needs the one-time indoor survey of the building; without it a phone indoors falls back to GPS and Wi-Fi with a long, unreliable tail. Floor-level indoor positioning is iOS today; Android joins in 2027.
A sealed Bluetooth Low Energy tag about the size of a coin, with a wipeable face and an adhesive or strap mount. It is designed to be attached once and then forgotten about.
The tag is in active development. Battery life, range and enclosure ratings will be published when they are measured on production hardware — not before.
NavvTrack is a subscription: $4 per device per month for the platform, with optional modules such as workflow and team messaging at $1 per device per month each. Indoor mapping, where you want floor-level positioning, is a one-time per-site fee.
There is no reader infrastructure to buy, so there is no capital line item — which is usually what stops an asset tracking project at budget review.
ECRI priced a single identical scenario — a 300-bed hospital, 3,000 tags, room-level accuracy — at $100,000 to $2 million depending purely on the tracking technology chosen.
Kontakt.io publishes $350 per licensed bed per year on its own ROI calculator, all-inclusive, on a three-to-five year term — priced per use case. CenTrak does not publish pricing.
Tag pricing will be set with our first design partners. Sources: ECRI SELECTplus via Health Facilities Management; Kontakt.io ROI calculator.
NavvTrack began on iOS because that is what most health systems standardised on for clinical mobility. Android support is on the roadmap for 2027, covering both managed Android devices in the fleet and Android handsets acting as readers for tags.
If you run a mixed estate, or you are standardising on Android for support services while clinical stays on iOS, tell us now — design partners shape the order we build in.
Expected accuracy on Android — these are engineering targets, not measurements, because it has not shipped. Android has no equivalent of the iOS indoor positioning layer, so we use two paths. Where your access points support Wi-Fi RTT (802.11mc/az) — most enterprise Wi-Fi 6 gear — Android’s own documentation puts ranging at 1–2 m, with no network connection required and three or more access points in range. Elsewhere we fall back to Wi-Fi and Bluetooth fingerprinting, which we expect to land in the 3–8 m range with a slower refresh: Android throttles apps to four Wi-Fi scans per two minutes in the foreground. Floor level comes from the barometer plus the fingerprint. We will publish measured numbers from the first Android pilot, the same way we do for iOS above.
Dated roadmap items are commitments we expect to keep, not guarantees. We will give design partners the real schedule.
No readers, gateways or ceiling sensors of ours, and no access-point upgrade. You need NavvTrack running on managed iPhones that move around the building, and a tag on each asset you want to see.
Two different numbers, and it is worth keeping them apart. The phone knows where it is to a median of about 2 m on a surveyed floor (measured figures above). A tag is placed relative to the phone that heard it, so a tagged asset resolves to a zone and a floor — enough to answer “which floor and which wing is this pump on”. It is not sub-metre, and it is not continuous in an empty corridor at 3am.
Then you already have guaranteed coverage where you installed it, and you should keep it for the use cases that need it. The usual reason to talk to us is the equipment outside that footprint — the assets that were never worth extending the reader grid to reach.
Yes. NavvTrack sits alongside your MDM rather than replacing it, and syncs inventory from Jamf Pro. See the Jamf integration guide.
Coming soon. The tag is in development and we are selecting design partners now for 2027. Existing NavvTrack customers get first access.
We are looking for a small number of health systems to shape the tag, the pricing and the rollout. If finding equipment is a problem you have given up on solving, that is exactly who we want to talk to.
