What would Triagents
release in your practice?
Enter your call volumes and we'll estimate the front-desk capacity your phones consume, what that capacity costs a year, and how much of it Triagents absorbs while answering 24/7. Pricing is by quotation: add the fee quoted to you and the page works out the net position.
| Coverage | Annual cost | Availability |
|---|---|---|
| Today: 4 front-desk staff | A$359,100 | Business hours |
| With Triagents: 1 receptionist + AI | A$89,775 + your quoted fee | 24/7 · calls that need a person warm-transferred during business hours |
| Difference | Enter your quoted fee to see the net figure | |
- After-hours calls a month
- 220
- Carrying booking intent (measured 47.2%)
- 104
- Bookings, at your conversion rate
- –
- Attended, at your attendance rate
- –
≈220 after-hours calls a month land while the desk is dark. In live Triagents data, 47.2% of after-hours calls carry booking intent; the rest are results enquiries, appointment changes and general questions. Enter your booking conversion and attendance rates to value the intent. We do not fill them in for you.
- Your referral base
- –
- Additional studies at the uplift you entered
- –
- Attended appointments a month that cover your quoted fee
- –
Enter your referrer count and studies per referrer to model this. We do not fill these in for you.
How this is worked out. The premise is that a practice which answers reliably keeps more of its referrers, but the size of that effect is yours to estimate, not ours to assert. The uplift percentage is yours, not ours. We publish no default, because nothing we have measured links answering performance to referral volume, and a figure we invented here would set the scale of everything in this panel. Additional studies are your referral base multiplied by the uplift you entered, valued at your average revenue per attended appointment. This forecast is not added to the capacity figures above or to the after-hours figure, because a saving we have modelled and a forecast you have parameterised are different things and should be read separately.
- Answered in two rings, 24/7Nights, weekends and public holidays included.
- Line capacity that matches your peakProvisioned at double your current lines, or as many as you need, so the Monday 8am surge is answered at once rather than queued one receptionist at a time.
- Lost calls answeredThe average imaging centre loses ~18% of inbound calls to engaged tones and voicemail. Each one is answered; what it becomes depends on your rules and availability.
- Referrer calls routed rightIdentified instantly and warm-transferred to reception or the on-call radiologist, by your rules, with full context.
- Front desk freed for patientsNo more juggling the phone and the counter, full attention on the person standing there.
- Emergency-awareEmergency vocabulary is recognised on the first exchange and the caller is told to hang up and call 000.
- Modality-aware bookingMRI, CT, ultrasound, contrast, prep and referral rules modelled per machine and per site.
- SMS confirmations with prepEvery booking confirmed by SMS with modality-specific prep instructions.
- Books from your website tooThe same triage brain answers web chat, not just the phone.
- No-shows recoveredWhere enabled in your configuration, outbound follow-up rebooks no-shows and chases unbooked referrals.
- No coverage gapsNo sick days, no leave, no re-hiring when someone moves on.
- Results vary by clinicResolution and booking outcomes depend on your existing operations, call mix and configured workflows, which is why this page models against your own inputs.
Indicative only. Triagents is priced by quotation from your site count, call and chat volume and configured scope; this page does not estimate the fee. Every figure above is built from your inputs and the staffing model stated beside them.
From the blog
What we are learning, written down.
- What can AI agents actually do in radiology?Not AI reading scans. What an AI agent actually does across reception, booking, referrals, capacity and follow-up, and what it must never touch.
- We called 100 radiology practices after hours. Here is what answered.Original research: the same 100 radiology practices, rung on Sunday evening. Not one reached a person, and eleven were answered by an AI agent.
- We called 100 radiology practices. Here is what we found.Original research: we rang 100 Australian radiology practices and timed every call. Eight reached a person straight away; the median wait was 90 seconds.
Book a radiology network assessment.
We'll map it to your network.
30 minutes with a solutions engineer. We model your call volume, centre count, and integrations, then show the AI agents running on your own scenarios, and answer everything compliance- and security-related upfront.