Intur is the post-installation adoption layer for complex medical equipment. Your customer scans a QR on the device and gets role-based guidance linked to the approved IFU. You get field intelligence you've never had.
Every bid says "training included." Yours says the device ships with its own adoption layer — and shows the buying hospital its adoption analytics.
"Included with [your device family]: a role-based adoption layer at the point of use — offline-capable, multilingual (en/de/fr) — with adoption analytics for the buying hospital."
Usability and training burden increasingly appear in hospital procurement criteria. An adoption layer is a direct answer to those line items — and one incremental tender win pays for years of Intur.
Every unit you sell stops adding to the support queue. Questions get answered at the device, not on a ticket — support scales without scaling headcount.
Cited answers from approved content only, a hard refusal of clinical advice, and an append-only audit trail you can export for a notified body.
Complex equipment ships with paper IFUs that are unavailable, inaccessible, or too long to scan during a clinical or technical procedure.
Manufacturers have no visibility into which steps users find unclear, what questions go unanswered, or where adoption is stalling across the installed base.
Support teams field calls and tickets for questions well-structured digital content could resolve right at the device — a cost that grows with every unit sold.
Installation sign-off and content approval lack structured digital records, creating risk for ISO 13485, SOC 2, and HIPAA audits.
Upload raw manufacturer materials. The pipeline extracts, structures, and creates role-variant draft content — a draft kit in under 24 hours.
Editors work a draft → in_review → approved queue with versioning and a diff against the source IFU. Only approved content ever reaches a user.
A QR on each device resolves to role-appropriate guidance, cited AI chat, and a feedback widget. Installers run a digital handover sign-off.
Every interaction feeds the Manufacturer Intelligence Loop. Spot feedback clusters across clinics, push an update, watch the question rate fall.
Cuts ticket volume and cost per device, and scales support without scaling headcount — turning post-sale from a cost centre into a differentiator.
Gets provable, exportable audit trails, a guarantee no unapproved content reaches a user, and an AI that stays inside the approved-content line.
Scans for the right step in seconds — no app, no login, in their language — fast enough that it beats guessing or calling for help.
An eIFU platform stores documents. Intur is an adoption layer on top of them: role-based guidance at the QR scan, cited AI chat over your approved content, and a Manufacturer Intelligence Loop that turns every interaction into field signal. It links to the approved IFU — it never replaces it.
Intur is an adoption layer — not a medical device and not labeling — and it is built to stay on the right side of that line. The AI answers only from approved content, carries a citation on every claim, and hard-refuses clinical advice. It also runs in a chat-off mode: QR landing, role-based content, handover and the dashboard all work without AI, as a compliance-safe baseline.
Adoption is the whole game, so it is built for the nurse between patients: a scan opens role-appropriate guidance in seconds with no app or login, in her language (en/de/fr on day one). If it is not faster than guessing or calling for help, it does not get used — so that is the bar we design to.
Yes. Versioning and approval are properties of the data model, not a bolt-on. There is an append-only signed audit log, a controlled draft → in_review → approved state machine, and per-role attested PDF handover records. ISO 13485 clause mapping and a SOC 2 controls inventory ship with it.
It is a working module, sold separately on top of the per-family subscription. Every scan, feedback tap, and AI query emits structured signal that aggregates into feedback clusters and device-family health cards. We demo it live on the first call. Validating its signal quality at low scan volume is exactly what the 90-day pilots are for.
One device family. 2–3 sites. 90 days. Outcome-based. We'll instrument support-contact deflection and time-to-competence from day one.
Thanks — we'll reach out to scope a pilot.
Scan the live demono app · no login · opens the demo ECG kit